CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Pre-harvest Sprouting via Regulation of GA Biosynthesis and Deactivation in Rice

CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Pre-harvest Sprouting via Regulation of GA Biosynthesis and Deactivation in Rice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Pre-harvest Sprouting via Regulation of GA Biosynthesis and Deactivation in Rice Man Bo Lee, Ha Neul Lee, Sang-Ho Chu, Yong-Jin Park, Jae Yoon Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6950427/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Pre-harvest sprouting (PHS), where seeds germinate on panicles before harvest under humid conditions, is a serious global issue in cereal crop production, including rice. OsERF94 was previously identified as a candidate gene associated with PHS through a genome-wide association study. In this study, we investigated the role of OsERF94 in PHS using CRISPR/Cas9 gene editing. The CRISPR/Cas9-mediated mutagenesis of OsERF94 induced frameshift mutations, resulting in a loss-of-function of OsERF94 in the 1-I-ET and 2-D-ET lines. The 1-I-ET and 2-D-ET lines exhibited significantly higher germination rates under PHS conditions compared to the wild type, indicating increased susceptibility to PHS. Whole-genome re-sequencing confirmed that few or no mutations could be detected at off-target candidate sites in both edited lines, ensuring the precision of the CRISPR/Cas9 gene editing. A transcriptome analysis revealed that OsERF94 modulates the expression of key GA biosynthetic and catabolic genes, including OsLOL1 , OsKO3 , OsGA3ox2 , and OsGA2ox5 , during both seed development and the early germination stages of PHS. The up-regulation of GA biosynthetic genes and the down-regulation of GA deactivation genes in both gene-edited lines likely led to elevated endogenous GA levels at 0 and 1 days after PHS, promoting germination under PHS conditions. These findings suggest that OsERF94 acts as a negative regulator of germination by modulating both GA biosynthesis and deactivation. Our findings contribute to expanding our knowledge of the molecular mechanisms of OsERF94 in PHS and highlight OsERF94 as a promising target for the genetic improvement of PHS resistance in rice-breeding programs. OsERF94 CRISPR/Cas9 Pre-harvest sprouting Germination GA biosynthesis GA deactivation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Pre-harvest sprouting (PHS) refers to a phenomenon where seeds germinate on the panicles before harvest under continuously rainy and humid weather (Li et al. 2004 ). PHS has become a serious global issue during the agricultural production of cereal crops such as rice, with the average annual financial loss due to PHS has been estimated to be one billion dollars worldwide (Tai et al. 2021 ; Hull et al. 2024 ). PHS also affects grain quality by enhancing the activity of oxidoreductases and hydrolases in cereal grains, resulting in the loss of nutrients such as starch, protein, and oil (Li et al. 2004 ). The eating and cooking quality of rice grains were lower in rice plants affected by PHS, as were the amylose and total starch contents (Zhang C et al. 2020 ). However, cultivated crops generally exhibit lower dormancy levels compared to their wild ancestors, which makes modern crop varieties more susceptible to PHS (Tai et al. 2021 ). Due to global climate change, heavy rainfall in specific regions can lead to more frequent occurrences of PHS (Hu et al. 2025 ). Therefore, developing PHS-resistant varieties has become a key objective in rice-breeding programs, alongside the discovery of PHS-resistant genes (Lee et al. 2021 ). PHS occurs primarily due to an imbalanced dormancy/germination ratio (Tai et al. 2021 ). Seed dormancy and germination are distinct biochemical and physiological processes regulated by various internal factors, such as plant hormones, carbohydrate metabolites, and reactive oxygen species (Hilhorst and Karssen 1992 ; Yu et al. 2016 ; Omoarelojie et al. 2022 ). Among plant hormones, abscisic acid (ABA) and gibberellin (GA) play critical roles in antagonistically controlling dormancy and germination (Yaish et al. 2010 ; Sohn et al. 2021 ). ABA promotes dormancy formation and maintenance, whereas GA induces germination by counteracting ABA effects on dormancy (Finkelstein et al. 2008 ). In rice, OsVP1 activates Sdr4 , a key regulator of pre-harvest sprouting, by binding to its promoter (Chen et al. 2021 ). OsVP1 and Sdr4 play roles in the biosynthesis and signaling pathways of ABA and GA, regulating seed dormancy. A rice mutant with delayed germination and semi-dwarfism was identified, caused by mutations in OsKO1 (Zhang H et al. 2020 ). The mutation inhibits GA biosynthesis, impairing starch mobilization and reducing ABA signaling, ultimately delaying seed germination. Ethylene also plays important roles in the regulation of dormancy and germination (Corbineau et al. 2014 ). The Arabidopsis reduced dormancy 3 mutant is caused by a loss-of-function mutant of the ethylene receptor ETHYLENE RESPONSE1 (ETR1) (Li et al. 2019 ). ETR1 regulates seed dormancy and germination partially through the DELAY OF GERMINATION1 pathway. Ethylene counteracts the inhibitory effects of ABA on germination by modulating ABA metabolism and signaling pathways (Linkies and Leubner-Metzger 2011 ). Additionally, ethylene and GA work synergistically to promote seed germination (Corbineau et al. 2014 ). Ethylene response factors (ERFs), a family of APETALA2/ETHYLENE RESPONSE FACTORS (AP2/ERFs), regulate genes involved in hormone and stress signaling (Müller and Munné-Bosch 2015 ; Phukan et al. 2017 ). Previously, we identified OsERF1 and OsERF94 through a genome-wide association study (GWAS) of PHS and germination from detached grains (Min et al. 2024 ). OsERF1 and OsERF94 were detected within a 100 kb region from the SNP marker Chr4_Pos27378200, which was detected in Manhattan plots for both traits. Furthermore, OsERF1 was functionally validated using the CRISPR-Cas9/HDR and geminiviral replicon system in rice (Kim et al. 2024 ). The ERF1-hdr line, which carries a 1 bp SNP and a 6 bp insertion in OsERF1 , exhibited enhanced seed dormancy and PHS resistance. Genes involved in ABA signaling, such as PYL , SnRK2 , ABI3 , ABI5 , and Sdr4 , were highly expressed in the ERF1-hdr line compared to the WT, whereas genes related to ethylene and GA signaling, such as EIN3 , GID1 , and GYMYB , showed reduced expression levels. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system has been extensively utilized for targeted gene editing in plants (Bortesi et al. 2016 ). In rice, CRISPR/Cas9 gene editing has been applied for gene-function analyses and for the development of stress-resistant varieties, including those resistant to PHS (Romero and Gatica-Arias 2019 ; Kim et al. 2024 ). The CRISPR/Cas9 gene editing of OsABA8ox resulted in frameshift mutations in gene-edited rice lines (Fu et al. 2022 ). Loss-of-function in OsABA8ox enhances seed dormancy by elevating endogenous ABA levels and modulating ABA signaling. Overexpression and CRISPR/Cas9 gene editing of OsMFT2 , which encodes a phosphatidylethanolamine-binding protein, resulted in different responses to PHS (Zhang et al. 2025 ). Overexpression lines exhibited strong seed dormancy and weak PHS, whereas gene-edited lines showed strong PHS. In this study, we applied CRISPR/Cas9 gene editing to OsERF94 , which was identified along with OsERF1 in our previous GWAS of PHS (Min et al. 2024 ), to investigate its function. OsERF94 gene-edited lines exhibited increased PHS compared to non-edited ‘Nipponbare’ plants. We conducted RNA sequencing of OsERF94 gene-edited lines and the WT to investigate the molecular mechanisms by which OsERF94 regulates PHS. OsERF94 , a PHS-resistant gene, can be utilized in molecular breeding programs to enhance PHS resistance in rice. Additionally, our transcriptome analysis provides valuable insights into the role of OsERF94 in regulating PHS. Results OsERF94 , a Candidate Gene Associated with Pre-harvest Sprouting in Rice A previous GWAS of PHS and detached grain germination was conducted using 127 cultivated rice accessions (Min et al. 2024 ). These accessions were subjected to whole-genome sequencing and variant calling to obtain genotype data. GWAS was conducted using a compressed mixed linear model in the GAPIT package. SNPs exceeding a –log 10 ( P -value) threshold of 5 were considered statistically significant. A total of 15 significant SNPs were associated with PHS, and 76 were linked to detached grain germination. The SNP marker Chr4_Pos27378200, located on chromosome 4 at position 27378200, was significantly associated with both traits. Within a 100 kb region surrounding the significant SNP, 25 genes were identified, including OsERF94 ( Os04g0547600 ). Subsequently, we investigated haplotypes of OsERF94 to examine the impact on PHS. Haplotype 1 of OsERF94 exhibits three SNPs, one of which results in a non-synonymous mutation (Table 1 ), whereas haplotype 6 shows the same sequence as the reference. PHS was significantly reduced in haplotype 1 compared to haplotype 6 (Fig. 1 ). GWAS and haplotype analyses suggested that OsERF94 is a candidate gene associated with PHS in rice. To validate this hypothesis, we generated OsERF94 loss-of-function mutants in the ‘Nipponbare’ background using CRISPR/Cas9 gene editing. Table 1 SNPs identified in haplotype 1 of OsERF94 Reference Substitution Amino acid change Mutation type Position on chromosome 4 #1 G C P to P Synonymous 27409430 #2 G A V to V Synonymous 27409520 #3 G A A to T Non-synonymous 27409731 Development of OsERF94 Mutant Lines via CRISPR/Cas9 OsERF94 contains a single exon, and three guide sequences were designed to target the exon for CRISPR/Cas9 gene editing (Fig. 2 A). The CRISPR-P v2.0 (Liu et al. 2017 ) and the CRISPR RGEN tools (Park et al. 2015 ) were used for guide sequence design. The two guide sequences of sgRNA1 and sgRNA2 target the same position on the target gene, but the first nucleotide (5′ end) of the guide sequence of sgRNA2 was changed to adenine instead of cytosine (as in sgRNA1 and the WT). The first nucleotide of the guide sequence of sgRNA3 was also changed to adenine. Each guide sequence was introduced into the pRGEB31 vector (Addgene #51295) and driven by the OsU3 promoter (Fig. 2 B). The expression levels of Cas9 and Hpt were driven by separate 35S promoters. A total of 81 transgenic plants were obtained through Agrobacterium -mediated transformation using mature seeds of ‘Nipponbare’. To identify mutations in OsERF94 , PCR was performed using OsERF94 -specific primers (Table S1 ) on T 0 plants, followed by Sanger sequencing of the PCR products. The mutation types of T 0 plants were determined by manually analyzing the Sanger sequencing results, which were then double-checked using the ICE tool (Roginsky 2018 ). The mutation efficiency of sgRNA1 was 25.64% (10 out of 39), whereas sgRNA2 exhibited a mutation efficiency rate of 72.73% (16 out of 22) (Table 2 ). These results suggest that the U3 promoter prefers adenine as the transcription initiation site. The mutation efficiency of sgRNA3 was 35.00% (7 out of 20). Heterozygous mutations (54.55%) were the most frequently found mutation type, with 18 heterozygous mutants identified among the 33 T 0 mutant lines (Table 3 ). Homozygous mutations were identified in five out of the 33 T 0 mutant lines. Among them, four lines harbored homozygous mutations induced by sgRNA2, while one line carried a homozygous mutation induced by sgRNA3. Table 2 Mutation efficiency rates of guide sequences Mutation efficiency (%) z sgRNA1 10/39 (25.64) sgRNA2 16/22 (72.73) sgRNA3 7/20 (35.00) z The mutation efficiency of each guide sequence was calculated by dividing the number of gene-edited plants by the number of transgenic plants Table 3 Analysis of Mutation Types in T 0 Mutant Plants Homozygous Heterozygous Bi-allelic Non-determined z Total No. of plants Rate (%) No. of plants Rate (%) No. of plants Rate (%) No. of plants Rate (%) No. of plants Rate (%) sgRNA1 0 0.00 8 80.00 2 20.00 0 0.00 10 sgRNA2 4 25.00 5 31.25 5 31.25 2 12.50 16 sgRNA3 1 14.29 5 71.43 0 0.00 1 14.29 7 Total 5 15.15 18 54.55 7 21.21 3 9.09 33 100.00 z Multi-alleic, chimera A T 0 heterozygous mutant line (#1-g2-C4) induced by sgRNA2 and a T 0 homozygous mutant line (#1-g3-C13) were advanced to the next generation. Cas9 -specific and Hpt -specific primers (Table S1 ) were used to identify transgene-free lines of T 1 #1-g2-C4 and T 1 #1-g3-C13, as the Cas9 gene is located near the right border, while the Hpt gene is located near the left border in the pRGEB31 vector (Fig. 2 B). PCR-negative lines were selected as transgene-free lines. To identify homozygous mutant lines among the transgene-free lines, Sanger sequencing was conducted. Transgene-free lines of T 1 #1-g2-C4 with a homozygous 1 bp insertion were designated as 1-I-ET, while transgene-free lines of T 1 #1-g3-C13 with a homozygous 2 bp deletion were designated as 2-D-ET (Fig. 3 A-D). The 1 bp insertion in 1-I-ET and the 2 bp deletion in 2-D-ET caused frameshift mutations in OsERF94 , leading to early termination (Fig. 3 E). The ethylene-responsive transcription factor domain is detected between the 102nd and 255th amino acids, and the AP2/ERF domain superfamily is detected between the 137th and 198th amino acids, as determined by InterProScan (Quevillon et al. 2005 ). Both the ethylene-responsive transcription factor and the AP2/ERF domain superfamily were removed from the prematurely terminated proteins of 1-I-ET and 2-D-ET, respectively. These results indicate the loss-of-function mutations of OsERF94 . Loss-of-function of OsERF94 Enhances Pre-harvest Sprouting To examine the PHS response based on the sampling timing, panicles were collected from ‘Nipponbare’ plants at five and six weeks after heading and were then subjected to germination experiments (Figs. 4 A, B). When panicles were collected at six weeks after heading, the germination rate was 89.43% at three days after the PHS treatment and exceeded 95% starting from four days after the PHS treatment (Fig. 4 C). The germination rates were significantly decreased at all time points except one day after PHS in WT panicles collected at five weeks after heading compared to those collected at six weeks. When panicles were collected at five weeks, the germination rate was 85.96% at seven days after the PHS treatment. Because the PHS experiment conducted at five weeks after heading allowed for a more precise observation of germination rates compared to the six-week experiment, subsequent PHS treatments were performed using panicles collected at five weeks after heading. To ascertain the involvement of OsERF94 in PHS in rice, OsERF94 gene-edited lines were used for the PHS treatment. Panicles were collected at five weeks after heading from 1-I-ET (ten panicles) and 2-D-ET (eleven panicles). The germination rates were significantly increased at all time points, except for that at one day after PHS in 1-I-ET and 2-D-ET compared to WT panicles collected at five weeks (Fig. 4 E). The germination rates of 1-I-ET and 2-D-ET at three days after the PHS treatment were 88.42% and 85.88%, respectively, similar to that (85.96%) of the WT at seven days. These results indicate that the loss-of-function of OsERF94 enhances susceptibility to PHS. On the other hand, no drastic phenotypic changes, such as severe dwarfism, were observed in either gene-edited line compared to the WT (Fig. S1 ). Plant height was slightly reduced in both gene-edited lines. Transcriptome Analysis of OsERF94 To the best of our knowledge, little is known about the expression of OsERF94 in rice. The expression patterns of OsERF94 across different tissues and developmental stages were examined using 80 rice RNA sequencing libraries available from the Rice Genome Annotation Project (RGAP, https://rice.uga.edu/index.shtml ) (Hamilton et al. 2025 ). According to RGAP DB, OsERF94 is relatively highly expressed during the seed development stage compared to the seedling, vegetative, and reproductive stages (Fig. 5 A). OsERF94 expression is particularly high in the endosperm and embryo and is also elevated in mature seeds under hypoxic conditions. Specifically, the embryo RNA sequencing data (SRR9002107 and SRR9002108) were obtained from ‘Nipponbare’ embryos collected at 15 days after pollination, consistent with the cultivar used in this study. To investigate the expression pattern of OsERF94 further during grain development, RNA samples were collected at weekly intervals for four consecutive weeks starting one week after heading. OsERF94 was highly expressed at three weeks after heading, and the expression level was significantly higher than that at one week after heading (Fig. 5 B). In contrast, OsERF94 was barely expressed at one and two weeks after heading, with CT values of qRT-PCR greater than 35. Therefore, we performed RNA sequencing using samples collected at three weeks after heading, when the expression level of OsERF94 was the highest. Using seeds collected three weeks after heading, RNA sequencing was conducted to investigate the role of OsERF94 in PHS. Differentially expressed genes (DEGs) were identified by comparing each gene-edited line with the WT, using a threshold of |fold change| ≥ 2 and false discovery rate (FDR) p -value ≤ 0.05. A total of 3445 DEGs were identified in 1-I-ET, consisting of 2733 up-regulated and 712 down-regulated genes (Fig. 5 C). In 2-D-ET, 4863 DEGs were identified, with 3413 up-regulated and 1450 down-regulated genes. The number of DEGs commonly identified in both 1-I-ET and 2-D-ET was 2878. To characterize the biological relevance, a MapMan analysis was conducted using the common DEGs (Fig. 5 D). The average fold change values of the common DEGs between 1-I-ET and 2-D-ET were used for the MapMan analysis (Thimm et al. 2004 ) and are presented as red (up-regulated) or blue (down-regulated) in the corresponding MapMan diagram. Within the ‘Regulation overview’ category, 21 DEGs were identified in the ‘GA’ subcategory, representing the largest number among the subcategories related to plant hormones. In the ‘ABA’ subcategory, 13 DEGs were identified, all of which were down-regulated. The majority of these DEGs were related to ribosomal subunits (Table S2). In addition, a number of common DEGs were identified in redox-related subcategories, such as ‘Heme’, ‘Glutaredoxin’, and ‘Dismutase/Catalase’. In the ‘Dismutase/Catalase’ subcategory, most of the DEGs were associated with the lignin biosynthesis pathway (Table S2). Several genes involved in GA biosynthesis and deactivation were identified among the common DEGs between 1-I-ET and 2-D-ET (Fig. 6 A). OsLOL1 ( AGIS_Os08g005160 ), OsKO3 ( AGIS_Os06g033220 ), and OsKAO ( AGIS_Os06g000950 ) are involved in GA biosynthesis, while OsEUI ( AGIS_Os05g035360 ) and OsGA2ox3 ( AGIS_Os01g047760 ) are involved in GA deactivation. All of the DEGs were up-regulated in both 1-I-ET and 2-D-ET. These results suggest that OsERF94 plays a role in controlling the GA content by regulating both GA biosynthesis and deactivation in developing seeds. Moreover, additional RNA sequencing was conducted on seeds collected at zero, one, and two days after PHS using panicles harvested five weeks after heading from WT, 1-I-ET, and 2-D-ET. Before PHS, the GA biosynthesis genes OsKO3 and OsKO4 ( AGIS_Os06g033150 ) were up-regulated in both 1-I-ET and 2-D-ET, while the GA deactivation gene OsGA2ox5 ( AGIS_Os07g000350 ) was down-regulated (Fig. 6 A). One day after PHS, the GA activation gene OsGA3ox2 ( AGIS_Os01g006890 ) was up-regulated in both 1-I-ET and 2-D-ET (Fig. 6 A). Two days after PHS, OsLOL1 , involved in GA biosynthesis, and OsGA2ox1 ( AGIS_Os05g005570 ), involved in GA deactivation, were both up-regulated in 1-I-ET and 2-D-ET (Fig. 6 A). These findings provide further support of the role of OsERF94 in regulating GA during the PHS response. Several genes involved in GA biosynthesis and deactivation were identified among the common DEGs between 1-I-ET and 2-D-ET (Fig. 6 A). One day after PHS, the GA activation gene OsGA3ox2 ( AGIS_Os01g006890 ) was up-regulated in both 1-I-ET and 2-D-ET (Fig. 6 A). Two days after PHS, OsLOL1 , involved in GA biosynthesis, and OsGA2ox1 ( AGIS_Os05g005570 ), involved in GA deactivation, were both up-regulated in 1-I-ET and 2-D-ET. These findings provide additional support for the role of OsERF94 in regulating GA during the PHS response. In addition to GA-related genes, several genes involved in ethylene biosynthesis were differentially expressed in both 1-I-ET and 2-D-ET (Fig. 6 B). OsACO5 ( AGIS_Os05g043260 ) and OsACS2 ( AGIS_Os04g043000 ) were down-regulated at zero and one day after PHS, respectively. In contrast, OsACS1 ( AGIS_Os03g044810 ) was highly up-regulated in both lines, with fold changes of 144.4 in 1-I-ET and 354.19 in 2-D-ET. These results suggest that OsERF94 also regulates the PHS response by modulating ethylene biosynthesis. Off-target Analysis in OsERF94 Gene-edited Lines We investigated whether the off-target effects of sgRNA2 and sgRNA3 resulted in mutations at off-target candidate sites in T 1 gene-edited lines. Off-target candidate sites of sgRNA2 and sgRNA3 (Table S3) were predicted using CRISPR-GE (Xie et al. 2017 ). Whole-genome re-sequencing was conducted on 1-I-ET (#1-g2-C4-31, sgRNA2), 2-D-ET (#1-g3-C13-4, sgRNA3), and the WT, and the reads were mapped to the ‘Nipponbare’ reference genome. Few or no mutations were identified in any of the off-target candidate sites in both gene-edited lines compared to the WT. In most of the mapped reads, the mapped sequences were identical to those of the reference genome, and only a very small number of reads contained nucleotide substitutions rather than deletions or insertions. These nucleotide substitutions were considered to be sequencing errors. The mapping results of both gene-edited lines for off-target candidates with an off-score greater than 0.1 are presented in Fig. S2. In this study, OsERF94 gene-edited lines were generated and validated to lack detectable off-target mutations. Discussion CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Susceptibility to Pre-harvest Sprouting CRISPR/Cas9 gene editing has been widely utilized in plant molecular research, as CRISPR/Cas9 enables precise and accurate modifications of target genes (Bortesi et al. 2016 ; Romero and Gatica-Arias 2019 ). We successfully induced mutations in OsERF94 via CRISPR/Cas9-mediated mutagenesis. In T 0 plants, the mutation efficiency rates across all three sgRNAs was 40.74%, with the mutation efficiency rates of sgRNA1 and sgRNA2 being 25.64% and 72.73%, respectively (Table 2 ). Only one nucleotide differed between the guide sequences of sgRNA1 and sgRNA2. While the guide sequence of sgRNA1 is a perfect match to OsERF94 , that of sgRNA2 has a single mismatch, where the cytosine at the 5′ end is substituted with adenine. The mutation efficiency of sgRNA2 was higher than that of sgRNA1 by 47.09%. It is known that the U3 promoter in the CRISPR/Cas9 vector initiates transcription at a defined adenine nucleotide (Belhaj et al. 2013 ). The guide sequence of sgRNA2 begins with adenine, which may lead to higher expression of sgRNA2 compared to sgRNA1, thereby resulting in higher mutation efficiency. After advancing a generation, we obtained scientifically reliable transgene-free homozygous gene-edited lines. To confirm transgene-free lines, we performed PCR screening using primers specific to Hpt (near the left border of the CRISPR vector) and Cas9 (near the right border). In transgene-free homozygous mutant lines, germination rates were significantly higher than those of the WT (Fig. 4 E), implying that the loss-of-function of OsERF94 increases susceptibility to PHS. Our results are consistent with our previous GWAS but appear to be inconsistent with the haplotype analysis of PHS (Fig. 1 ). It seems that the non-synonymous mutation in haplotype 6 enhances PHS resistance in rice, similar to the PHS-resistant allele of OsERF1 , which carries a non-synonymous mutation and a 6 bp insertion (Kim et al. 2024 ). The CRISPR-Cas9/HDR and geminiviral replicon system was applied to ‘Dongjin’, which does not contain either the non-synonymous mutation or the 6 bp insertion, resulting in the ERF1-hdr line carrying both mutations. PHS resistance was enhanced in the ERF1-hdr line compared to ‘Dongjin’. Prime editing or CRISPR-Cas9/HDR gene editing could also be employed in ‘Nipponbare’ to determine whether OsERF94 haplotype 6 confers PHS resistance. In the present study, CRISPR/Cas9 gene editing of OsERF94 induced early termination, which is expected to abolish the OsERF94 function entirely through complete gene knockout. As shown in Fig. 1 , if the gene-edited lines had the haplotype 1 variant, they may exhibit enhanced resistance to PHS. However, because our lines represent a complete knockout, it is possible that they are even more susceptible to PHS than the haplotype 6 lines, which are already known to be PHS-susceptible. Loss-of-Function of OsERF94 Promotes PHS by Modulating GA Biosynthetic and Catabolic Genes OsERF94 was involved in regulating both the biosynthesis and deactivation of GAs during seed development. At three weeks after heading, the GA biosynthesis-related genes OsLOL1 , OsKO3 , and OsKAO , as well as the GA deactivation-related gene OsEUI , were all up-regulated in both 1-I-ET and 2-D-ET (Fig. 6 A). OsLOL1, a C2C2-type finger protein, participates in GA biosynthesis, influencing seed germination in rice (Wu et al. 2014 ). OsLOL1 interacts with OsbZIP58, leading to the activation of the OsKO2 gene, a key gene in GA biosynthesis (Wu et al. 2014 ). A homolog of OsKO2 , OsKO3 , also participates in the GA biosynthesis pathway (Chen et al. 2019 ). The CRISPR/Cas9-mediated OsKO3 knockout line exhibited delays in both germination and seminal root growth (Chen et al. 2019 ). An exogenous GA treatment partially rescued the root growth defect, indicating that the defect is associated with the GA pathway. OsKAO plays a critical role in GA biosynthesis by catalyzing the formation of GA 12 (Sakamoto et al. 2004 ). Unlike other GA-metabolic enzymes encoded by multigene families, OsKAO is represented by a single gene in rice. Mutation of OsKAO resulted in a severely dwarfed phenotype and led to a substantial reduction in downstream GAs, including the complete absence of GA 1 in the oskao-1 mutant (Sakamoto et al. 2004 ). OsLOL1 , OsKO3 , and OsKAO play important roles in GA biosynthesis in rice, and the up-regulation of these genes in both gene-edited lines can contribute to a reduced dormancy level by promoting GA accumulation. However, OsEUI , a GA catabolic gene, catalyzes the 16 α ,17-epoxidation of non-13-hydroxylated GAs (Zhu et al. 2006 ). OsEUI reduces the activity of bioactive GA 4 in rice, demonstrating its role as a GA deactivating enzyme. Given that OsEUI has been reported to suppress GA accumulation and promote seed dormancy, its up-regulation in both gene-edited lines in our study likely contributes to an enhanced level of dormancy by reducing GA accumulation. These findings suggest that OsERF94 regulates GA levels in developing seeds by modulating both GA biosynthesis and catabolism, thereby contributing to the balance between seed dormancy and the germination potential. OsERF94 regulated seed germination by modulating both GA biosynthesis and deactivation at zero, one, and two days after PHS using panicles harvested five weeks after heading. At five weeks after heading (before PHS), OsKO3 and its homolog OsKO4 were up-regulated in both gene-edited lines, while the GA deactivation gene OsGA2ox5 was down-regulated (Fig. 6 A). GA 2-oxidases play a key role in the GA catabolic pathway, and OsGA2ox5 , a member of the C 20 -GA2ox subfamily, acts on GA 12 and GA 53 to produce GA 110 and GA 97 , respectively (Dong and Zeevaart 2005 ; Shan et al. 2014 ). OsGA2ox5 overexpression was shown to result in dwarfism and GA-deficient phenotypes in rice (Shan et al. 2014 ). Moreover, OsGA3ox2 , which is involved in the production of bioactive GAs, was up-regulated in both gene-edited lines one day after PHS (Fig. 6 A). OsGA3ox2 encodes an active GA 3β-hydroxylase that catalyzes the conversion of GA 20 and GA 9 into GA 1 and GA 4 , respectively, and is expressed in germinating rice seeds (Itoh et al. 2001 ). The up-regulation of GA biosynthesis genes OsKO3 , OsKO4 , and OsGA3ox2 , along with the down-regulation of the GA catabolic gene OsGA2ox5 , likely contributed to increased endogenous GA in seeds, thereby breaking dormancy and promoting germination. The differential expression levels of GA biosynthetic and catabolic genes in the gene-edited lines accelerated germination under PHS conditions. Germination rates were sharply and significantly increased from two days after PHS in both gene-edited lines compared to those of the WT (Fig. 5 E). Taken together, the loss-of-function of OsERF94 promotes PHS by modulating GA biosynthesis and catabolism during the early stages of germination. At two days after PHS, the GA biosynthesis gene OsLOL1 was up-regulated in both gene-edited lines (Fig. 6 ). The up-regulation of OsLOL1 can positively affect PHS. OsLOL1 exhibited high expression in seeds at one day after imbibition (Wu et al. 2014 ). In OsLOL1 antisense lines, germination was delayed by three to four days compared to the WT, and the endogenous GA content in imbibed seeds was significantly lower than in the WT. In contrast, the GA deactivation gene OsGA2ox1 was also up-regulated at two days after PHS (Fig. 6 A). At zero and one days after PHS, the up-regulation of GA biosynthesis genes and the down-regulation of the GA catabolic gene likely led to an increase in endogenous GA levels in the seeds of gene-edited lines. Subsequently, the expression of the GA deactivation gene OsGA2ox1 was up-regulated at two days after PHS, possibly as a feedback response to elevated GA levels, acting to fine-tune GA homeostasis. The differential expression levels of ethylene biosynthesis genes in both OsERF94 gene-edited lines under PHS conditions appear to contribute to seed germination. Endosperm rupture during seed germination stems from embryo growth and the weakening of the endosperm cap (Zhang et al. 2014 ). In Sisymbrium officinale , SoACS7 was not expressed before endosperm rupture but was strongly expressed when rupture reached 50–100% (Iglesias-Fernández and Matilla 2010 ). In our study, seed germination was defined as the point at which the coleoptile length exceeded 2 mm. One day after PHS, the germination rates of 1-I-ET, 2-D-ET, and the WT were 0.32%, 0%, and 0%, respectively (Fig. 4 E). Two days after PHS, the germination rates increased to 58.44% in 1-I-ET, 42.79% in 2-D-ET, and 12.46% in the WT. These results suggest that endosperm rupture occurred more frequently in the gene-edited lines than in the WT on the second day after PHS. Moreover, OsACS1 was strongly up-regulated in both gene-edited lines at two days after PHS (Fig. 6 B). The gene expression patterns of GA biosynthesis genes ( SoGA3ox2 , SoGA20ox2 , and SoGA2ox6 ) and ethylene biosynthesis genes ( SoACO2 and SoACS7 ) were analyzed during seed germination in Sisymbrium officinale (Iglesias-Fernández and Matilla 2010 ). Seed samples were collected at 0, 6, 12, 18, 20, 22, and 26 hours of germination. Endosperm rupture was observed at 20 hours, reached approximately 50% at 22 hours, and was nearly complete by 26 hours. SoGA3ox2 was strongly expressed at six hours of imbibition, but its expression declined afterward, maintaining about half the level from 12 to 26 hours. In contrast, SoGA2ox6 transcripts were barely detectable at six hours but peaked at 20 and 26 hours. SoACS7 was not expressed before endosperm rupture but showed strong expression at 22 and 26 hours. In our study, OsGA3ox2 was up-regulated one day after PHS in both OsERF94 gene-edited lines, while OsGA2ox1 and OsACS1 were strongly up-regulated two days after PHS. This sequential up-regulation pattern of OsGA3ox2 , OsGA2ox1 , and OsACS1 in OsERF94 gene-edited lines, together with the observed germination rates under PHS conditions, closely resembles the sequential expression pattern of SoGA3ox2 , SoGA2ox6 , and SoACS7 during seed germination in Sisymbrium officinale . These findings imply that GA functions earlier than ethylene in the regulation of seed germination. The loss-of-function of OsERF94 influences seed germination by modulating the expression of genes involved in GA and ethylene biosynthesis. In conclusion, our study demonstrates that the loss-of-function of OsERF94 significantly promotes PHS in rice by modulating the expression of GA biosynthetic and catabolic genes. OsERF94 appears to regulate GA accumulation during both seed development and the early stages of germination. The altered expression levels of key GA-related genes, specifically OsLOL1 , OsKO3 , OsGA3ox2 , and OsGA2ox5 , suggest a coordinated mechanism by which OsERF94 balances dormancy and the germination potential. To the best of our knowledge, little is known about the expression patterns and functional roles of ERF94 in rice or other plant species. Our findings contribute to a better understanding of the role of ERF94 in the hormonal regulation of seed germination. In addition, two PHS-associated genes ( OsERF1 and OsERF94 ) were identified near the SNP marker Chr4_Pos27378200, providing valuable insights for rice-breeding programs aiming to improve PHS resistance. Materials and Methods Plant Materials and Pre-harvest Sprouting Screening Rice cultivar ‘Nipponbare’ ( Oryza sativa L., spp. japonica ) plants were grown in a growth chamber maintained under 12 hours of light (29 ± 1°C) and 12 hours of darkness (23 ± 1°C). Panicles were collected at 35 and 42 days after heading (DAH) from WT and at 35 DAH from mutant lines induced by CRISPR/Cas9 for PHS screening. The primary branch of the panicle was cut and placed on autoclaved Whatman filter paper No. 1 (Whatman, Little Chalfont, UK) in a petri dish (150 × 20 mm), after which an amount of 30 ml of tap water was added to the petri dish. The lid was covered to maintain humidity. The petri dishes, covered with the lids, were placed in a growth chamber maintained at 12 hours of light (29°C, ± 1) and 12 hours of darkness (23°C, ± 1). Germination was evaluated every day for seven days using plump seeds, excluding sterile seeds. Seeds were evaluated as germinated when the length of the coleoptile exceeded 2 mm. CRISPR/Cas9 Vector Construction and Rice Transformation Guide sequence candidates targeting OsERF94 ( Os04g0547600 ) were designed using the CRISPR-P v2.0 (Liu et al. 2017 ) and the CRISPR RGEN tools (Park et al. 2015 ). Two exon regions of OsERF94 (5′– CTATGTCGTGGCAAGAGCAG CGG − 3′ and 5′– CCC GCCTATGTCGTGGCAAGAGC − 3′, PAM regions are indicated in bold) were used to design the guide sequences. A total of three guide sequences (sgRNA1 : 5′– CTATGTCGTGGCAAGAGCAG − 3′; sgRNA2 : 5′– aTATGTCGTGGCAAGAGCAG − 3′; 5′– aCTCTTGCCACGACATAGGC − 3′) were designed for CRISPR/Cas9 vector construction using the pRGEB31 plasmid (addgene, #51295). The OsU3 promoter drives the single guide RNA in the pRGEB31 vector. The first nucleotide of sgRNA2 and sgRNA3 was changed to A. sgRNA1 and sgRNA2 target the same position in the OsERF94 exon. Each guide sequence was introduced into the pRGEB31 vector. The CRISPR/Cas9 vectors for OsERF94 gene editing were transformed into the Agrobacterium strain EHA105 by a freeze–thaw method (Chen et al. 1994 ). Agrobacterium -mediated transformation using mature seeds of ‘Nipponbare’ was conducted, as described in earlier work (Lee et al. 1999 ). Transformed calli were selected on callus induction media containing 30 mg L − 1 of hygromycin during the first round of selection, and on media containing 50 mg L − 1 of hygromycin during the second round. Shoots were regenerated on shoot induction media containing 50 mg L − 1 of hygromycin at 28℃ under a light/dark cycle (12 hours of day/12 hours of night). Identification of Gene-Edited Mutants Genomic DNA was extracted from young leaves of putative transgenic plants using the HiGene™ Genomic DNA Prep kit (BIOFACT, Seoul, Republic of Korea) according to the manufacturer's instructions. PCR was conducted to detect transgenic plants with Cas9 -specific primers. To identify mutations in OsERF94 , PCR was conducted with OsERF94 -specific primers using T 0 plants, followed by Sanger sequencing of the PCR products. Mutation types of T 0 plants, such as heterozygous mutation and homozygous mutation, were distinguished by manually analyzing the Sanger sequencing results and were double-checked using the ICE (Inference of CRISPR Edits) tool (Roginsky 2018 ). The list of primers for PCR is available in Table S1 . PCR was carried out with TaKaRa Ex Taq (Takara Bio, Otsu, Japan) under the following conditions: 95°C for 5 min, followed by 30 cycles of 95°C for 30 sec, 56–62°C for 30 sec, and 72°C for 1 min, with a final extension at 72°C for 5 min. To obtain transgene-free homozygous mutants, genomic DNA was extracted from young leaves of T 1 plants, and PCR was performed with the Cas9 -specific primers and Hpt -specific primers. The list of primers for PCR is available in Table S1 . PCR-negative plants were selected and used for further PCR with the OsERF94 -specific primers. Sanger sequencing results of the PCR products were analyzed manually and double-checked using the ICE tool. RNA Extraction and Quantitative Real‑time PCR Hulled seeds were collected at 7, 14, 21, 28 DAH from ‘Nipponbare’ and were frozen in liquid nitrogen. The seeds were ground into a fine powder using a mortar and pestle. Total RNA was extracted using the Ribospin™ Seed/Fruit kit (Geneall, Seoul, Republic of Korea) following the manufacturer’s instructions. RNA was converted to cDNA by reverse transcription using oligo (dT) primers with the Power cDNA Synthesis Kit (iNtRON Biotechnology, Seoul, Republic of Korea). To evaluate the expression of the OsERF94 gene during seed development, qRT-PCR was performed with the RealMOD™ Green W 2 2x qPCR mix (iNtRON Biotechnology, Seoul, Republic of Korea) on a Rotor-Gene Q machine (QIAGEN, Hilden, Germany). The qRT-PCR conditions were 95℃ for 10 min followed by 40 cycles of 95℃ for 20 sec, 60℃ for 40 sec, and 72°C for 20 sec, with a final extension at 72°C for 5 min. Gene expression levels were normalized to OsACT1 ( Os03g0718100 ). The primer information is presented in Table S1 . Total RNA was extracted from three panicles as biological replicates, and qRT-PCR was conducted with three technical replicates for each sample. Gene expression levels were quantified using the 2 −ΔΔCT method (Livak and Schmittgen 2001 ). RNA sequencing Seeds were collected at 21 DAH from 1-I-ET, 2-D-ET, and the WT, with three biological replicates for each line. Total RNA was isolated using the Ribospin™ Seed/Fruit kit (Geneall, Seoul, Republic of Korea) according to the manufacturer’s instructions. The total RNA concentration was measured using the Quant-iT RiboGreen RNA Assay kit (Invitrogen, MA, USA). RNA integrity was examined using the TapeStation RNA ScreenTape system (Agilent, CA, USA). High-quality RNA samples with an RIN greater than 7.0 were used to prepare libraries, with 0.5 µg of total RNA per sample, using the TruSeq Stranded Total RNA Library Prep Plant kit (Illumina, CA, USA). Libraries were quantified using the KAPA Library Quantification kit (Kapa Biosystems, MA, USA), and the quality of libraries was evaluated using the D1000 ScreenTape system (Agilent, CA, USA). Indexed libraries were then sequenced in paired-end mode (2×150 bp) on an Illumina HiSeq X Ten (Illumina, CA, USA). Adapter sequences and low-quality bases were removed using Trimmomatic v0.38 (Bolger et al. 2014 ). Cleaned reads were aligned to the Oryza sativa T2T-NIP reference genome using HISAT2 v2.1.0 (Shang et al. 2023 ). SAM files were sorted and indexed using SAMtools v1.9 (Li et al. 2009 ) and transcript assembly and quantification were performed using StringTie v2.1.3b (Pertea et al. 2015 ). The gene expression analysis was conducted using DESeq2 (Love et al. 2014 ). DEGs were identified based on the criteria of |fold change| ≥ 2 and FDR p -value < 0.05. For the MapMan analysis (Thimm et al. 2004 ), bincode mapping was conducted using the Mercator webtool ( https://www.plabipd.de/portal/mercator-sequence-annotation ) (Lohse et al. 2014 ). Common DEGs between 1-I-ET and 2-D-ET were selected, and common DEGs with an average fold change greater than 2 were subjected to a MapMan analysis to identify affected metabolic pathways. Additionally, seeds were collected at zero, one, and two days after the PHS treatment using panicles harvested at five weeks after heading from 1-I-ET, 2-D-ET, and the WT, with two biological replicates for each line. Total RNA was extracted from each line and was used for RNA sequencing on the same platform described above. DEGs were identified using the criteria of |fold change| ≥ 2 and p -value < 0.05. Potential Off-targets and Whole-genome Re-sequencing Potential off-targets of sgRNA2 and sgRNA3 were predicted using CRISPR-GE (Xie et al. 2017 ). Two transgene-free homozygous mutant lines, 1-I-ET-31 (#1-g2-C4-31) and 2-D-ET-4 (#1-g3-C13-4), and the WT were used for whole-genome re-sequencing to search for off-targets. Genomic DNA (100 ng) was fragmented and subsequently used for library preparation with the TruSeq Nano DNA Library Prep kit (Illumina, CA, USA) following the manufacturer’s protocol. The quality of libraries was examined via electrophoresis using the Agilent High Sensitivity DNA kit (Agilent, CA, USA). Library quantification was performed using the KAPA Library Quantification kit (Kapa Biosystems, MA, USA) according to the manufacturer’s protocol. Sequencing was conducted in paired-end mode (2×150 bp) on the Illumina NovaSeq X Plus platform (Illumina, CA, USA). The quality of the raw data was evaluated using FastQC. Low-quality reads were trimmed with Cutadapt using a Q20 cutoff and a minimum remaining length of 15 bp. The resulting clean reads were then aligned to the ‘Nipponbare’ reference genome (available at http://www.ricesuperpir.com/web/nip ) (Shang et al. 2023 ) using BWA and were visualized with Geneious Prime v2023.0.4. Abbreviations ABA Abscisic acid AP2 APETALA2 DAH Days after heading DEG Differentially expressed gene ERF Ethylene response factor FDR False discovery rate GA Gibberellin GWAS Genome-wide association study PHS Pre-harvest sprouting RGAP Rice Genome Annotation Project Declarations Supplementary Information The online version contains supplementary materials. Acknowledgements The authors sincerely appreciate Dr. Laehyeon Cho and his lab members (Pusan National University, Republic of Korea) for their technical support with rice tissue culturing. Author Contributions SHC, YJP, and JYK developed the original concept of the project, and MBL and JYK designed the experiments. MBL generated the CRISPR/Cas9 gene-edited lines and conducted the majority of the experiments. HNL participated in the identification of gene-edited lines and in the qRT-PCR analysis. MBL drafted the manuscript, and all the authors contributed to manuscript revision and approved the submitted version. Funding This research was funded by the R&D program for Rural Development Administration (RDA), Republic of Korea (Project No. RS-2024-00322431), the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (Project No. 2022R1A4A1030348). Data Availability The datasets generated during this study are available from the corresponding author upon reasonable request. Ethics Approval and Consent to Participate Not applicable. Consent for Publication Not applicable. Conflict of Interest The authors declare that they have no conflicts of interest. References Belhaj K, Chaparro-Garcia A, Kamoun S, Nekrasov V (2013) Plant genome editing made easy: Targeted mutagenesis in model and crop plants using the CRISPR/Cas system. Plant Methods 9:1–10. https://doi.org/10.1186/1746-4811-9-39/TABLES/2 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. https://doi.org/10.1093/BIOINFORMATICS/BTU170 Bortesi L, Zhu C, Zischewski J, Perez L, Bassié L, Nadi R, Forni G, Lade SB, Soto E, Jin X, Medina V, Villorbina G, Muñoz P, Farré G, Fischer R, Twyman RM, Capell T, Christou P, Schillberg S (2016) Patterns of CRISPR/Cas9 activity in plants, animals and microbes. Plant Biotechnol J 14:2203–2216. https://doi.org/10.1111/PBI.12634 Chen H, Nelson RS, Sherwood JL (1994) Enhanced recovery of transformants of Agrobacterium tumefaciens after freeze-thaw transformation and drug selection. Biotechniques 16:664–668 Chen W, Wang W, Lyu Y, Wu Y, Huang P, Hu S, Wei X, Jiao G, Sheng Z, Tang S, Shao G, Luo J (2021) OsVP1 activates Sdr4 expression to control rice seed dormancy via the ABA signaling pathway. Crop J 9:68–78. https://doi.org/10.1016/J.CJ.2020.06.005 Chen X, Tian X, Xue L, Zhang X, Yang S, Brian Traw M, Huang J (2019) CRISPR-Based Assessment of Gene Specialization in the Gibberellin Metabolic Pathway in Rice. Plant Physiol 180:2091–2105. https://doi.org/10.1104/PP.19.00328 Corbineau F, Xia Q, Bailly C, El-Maarouf-Bouteau H (2014) Ethylene, a key factor in the regulation of seed dormancy. Front Plant Sci 5:113486. https://doi.org/10.3389/FPLS.2014.00539/PDF Dong JL, Zeevaart JAD (2005) Molecular Cloning of GA 2-Oxidase3 from Spinach and Its Ectopic Expression in Nicotiana sylvestris. Plant Physiol 138:243–254. https://doi.org/10.1104/PP.104.056499 Finkelstein R, Reeves W, Ariizumi T, Steber C (2008) Molecular aspects of seed dormancy. Annu Rev Plant Biol 59:387–415. https://doi.org/10.1146/ANNUREV.ARPLANT.59.032607.092740/CITE/REFWORKS Fu K, Song W, Chen C, Mou C, Huang Y, Zhang F, Hao Q, Wang P, Ma T, Chen Y, Zhu Z, Zhang M, Tong Q, Liu X, Jiang L, Wan J (2022) Improving pre-harvest sprouting resistance in rice by editing OsABA8ox using CRISPR/Cas9. Plant Cell Rep 41:2107–2110. https://doi.org/10.1007/S00299-022-02917-3/METRICS Hamilton JP, Li C, Buell CR (2025) The rice genome annotation project: an updated database for mining the rice genome. Nucleic Acids Res 53:D1614–D1622. https://doi.org/10.1093/NAR/GKAE1061 Hilhorst HWM, Karssen CM (1992) Seed dormancy and germination: the role of abscisic acid and gibberellins and the importance of hormone mutants. Plant Growth Regul 11:225–238. https://doi.org/10.1007/BF00024561/METRICS Hull SI, Swanepoel PA, Botes WC (2024) A critical review of the factors influencing pre-harvest sprouting of wheat. Agron J 116:3354–3367. https://doi.org/10.1002/AGJ2.21701 Hu Y, Sang Y, Li M, Hu W, Liu B, Huang P, Kang D, Liu Y, Min D, Song Y (2025) J Agron Crop Sci 211:e70041. https://doi.org/10.1111/JAC.70041 . Evaluating Wheat Pre-Harvest Sprouting Risk Using Indicator Based on Meteorological Data From 1981 to 2020 in China Iglesias-Fernández R, Matilla AJ (2010) Genes involved in ethylene and gibberellins metabolism are required for endosperm-limited germination of Sisymbrium officinale L. seeds. Planta 231:653–664. https://doi.org/10.1007/S00425-009-1073-5/FIGURES/5 Itoh H, Ueguchi-Tanaka M, Sentoku N, Kitano H, Matsuoka M, Kobayashi M (2001) Cloning and functional analysis of two gibberellin 3β-hydroxylase genes that are differently expressed during the growth of rice. Proc Natl Acad Sci U S A 98:8909–8914. https://doi.org/10.1073/PNAS.141239398/ASSET/D7E87D9D-B4FD-4755-89A9-A776421F9723/ASSETS/GRAPHIC/PQ1412393004.JPEG Kim JH, Yu J, Kim JY, Park YJ, Bae S, Kang KK, Jung YJ (2024) Phenotypic characterization of pre-harvest sprouting resistance mutants generated by the CRISPR/Cas9-geminiviral replicon system in rice. BMB Rep 57:79. https://doi.org/10.5483/BMBREP.2023-0210 Lee JS, Chebotarov D, McNally KL, Pede V, Setiyono TD, Raquid R, Hyun WJ, Jeung JU, Kohli A, Mo Y (2021) Novel sources of pre-harvest sprouting resistance for japonica rice improvement. Plants 10:1709. https://doi.org/10.3390/PLANTS10081709/S1 Lee S, Jeon J-S, Jung K-H, An G (1999) Binary vectors for efficient transformation of rice. J Plant Biology 42:310–316. https://doi.org/10.1007/BF03030346 Li C, Ni P, Francki M, Hunter A, Zhang Y, Schibeci D, Li H, Tarr A, Wang J, Cakir M, Yu J, Bellgard M, Lance R, Appels R (2004) Genes controlling seed dormancy and pre-harvest sprouting in a rice-wheat-barley comparison. Funct Integr Genomics 4:84–93. https://doi.org/10.1007/S10142-004-0104-3/FIGURES/7 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079. https://doi.org/10.1093/BIOINFORMATICS/BTP352 Linkies A, Leubner-Metzger G (2011) Beyond gibberellins and abscisic acid: how ethylene and jasmonates control seed germination. Plant Cell Rep 31:253–270. https://doi.org/10.1007/S00299-011-1180-1 Liu H, Ding Y, Zhou Y, Jin W, Xie K, Chen LL (2017) CRISPR-P 2.0: An Improved CRISPR-Cas9 Tool for Genome Editing in Plants. Mol Plant 10:530–532. https://doi.org/10.1016/j.molp.2017.01.003 Livak KJ, Schmittgen TD (2001) Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2 – ∆∆CT Method. Methods 25:402–408. https://doi.org/10.1006/METH.2001.1262 Li X, Chen T, Li Y, Wang Z, Cao H, Chen F, Li Y, Soppe WJ, Li W, Liu Y (2019) ETR1/RDO3 Regulates Seed Dormancy by Relieving the Inhibitory Effect of the ERF12-TPL Complex on DELAY OF GERMINATION1 Expression. Plant Cell 31:832–847. https://doi.org/10.1105/TPC.18.00449 Lohse M, Nagel A, Herter T, May P, Schroda M, Zrenner R, Tohge T, Fernie AR, Stitt M, Usadel B (2014) Mercator: A fast and simple web server for genome scale functional annotation of plant sequence data. Plant Cell Environ 37:1250–1258. https://doi.org/10.1111/PCE.12231/SUPPINFO Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:1–21. https://doi.org/10.1186/S13059-014-0550-8/FIGURES/9 Min MH, Khaing AA, Chu SH, Nawade B, Park YJ (2024) Exploring the genetic basis of pre-harvest sprouting in rice through a genome-wide association study-based haplotype analysis. J Integr Agric 23:2525–2540. https://doi.org/10.1016/J.JIA.2023.12.004 Müller M, Munné-Bosch S (2015) Ethylene Response Factors: A Key Regulatory Hub in Hormone and Stress Signaling. Plant Physiol 169:32–41. https://doi.org/10.1104/PP.15.00677 Omoarelojie LO, Kulkarni MG, Finnie JF, van Staden J (2022) Smoke-derived cues in the regulation of seed germination: are Ca2+-dependent signals involved? Plant Growth Regul 97:343–355. https://doi.org/10.1007/S10725-021-00745-1/METRICS Park J, Bae S, Kim JS (2015) Cas-Designer: a web-based tool for choice of CRISPR-Cas9 target sites. Bioinformatics 31:4014–4016. https://doi.org/10.1093/BIOINFORMATICS/BTV537 Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL (2015) StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33:290–295. https://doi.org/10.1038/nbt.3122 Phukan UJ, Jeena GS, Tripathi V, Shukla RK (2017) Regulation of Apetala2/Ethylene response factors in plants. Front Plant Sci 8:238455. https://doi.org/10.3389/FPLS.2017.00150/PDF Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R, Mulder J, Attwood TK, Bairoch A, Bateman A, Binns D, Bradley P, Bork P, Bucher P (2005) InterProScan: protein domains identifier. Nucleic Acids Res 33:W116–W120. https://doi.org/10.1093/NAR/GKI442 Roginsky J (2018) Analyzing CRISPR editing results. Genetic Eng Biotechnol News 38:S24–S26. https://doi.org/10.1089/GEN.38.11.13/ASSET/GEN.38.11.13.FP.PNG_V03 Romero FM, Gatica-Arias A (2019) CRISPR/Cas9: Development and Application in Rice Breeding. Rice Sci 26:265–281. https://doi.org/10.1016/J.RSCI.2019.08.001 Sakamoto T, Miura K, Itoh H, Tatsumi T, Ueguchi-Tanaka M, Ishiyama K, Kobayashi M, Agrawal GK, Takeda S, Abe K, Miyao A, Hirochika H, Kitano H, Ashikari M, Matsuoka M (2004) An Overview of Gibberellin Metabolism Enzyme Genes and Their Related Mutants in Rice. Plant Physiol 134:1642–1653. https://doi.org/10.1104/PP.103.033696 Shan C, Mei Z, Duan J, Chen H, Feng H, Cai W (2014) OsGA2ox5, a Gibberellin Metabolism Enzyme, Is Involved in Plant Growth, the Root Gravity Response and Salt Stress. PLoS ONE 9:e87110. https://doi.org/10.1371/JOURNAL.PONE.0087110 Shang L, He W, Wang T, Yang Y, Xu Q, Zhao X, Yang L, Zhang H, Li X, Lv Y, Chen W, Cao S, Wang X, Zhang B, Liu X, Yu X, He H, Wei H, Leng Y, Shi C, Guo M, Zhang Z, Zhang B, Yuan Q, Qian H, Cao X, Cui Y, Zhang Q, Dai X, Liu C, Guo L, Zhou Y, Zheng X, Ruan J, Cheng Z, Pan W, Qian Q (2023) A complete assembly of the rice Nipponbare reference genome. Mol Plant 16:1232–1236. https://doi.org/10.1016/j.molp.2023.08.003 Sohn SI, Pandian S, Kumar TS, Zoclanclounon YAB, Muthuramalingam P, Shilpha J, Satish L, Ramesh M (2021) Seed Dormancy and Pre-Harvest Sprouting in Rice—An Updated Overview. Int J Mol Sci 22:11804. https://doi.org/10.3390/IJMS222111804 Tai L, Wang HJ, Xu XJ, Sun WH, Ju L, Liu WT, Li WQ, Sun J, Chen KM (2021) Pre-harvest sprouting in cereals: genetic and biochemical mechanisms. J Exp Bot 72:2857–2876. https://doi.org/10.1093/JXB/ERAB024 Thimm O, Bläsing O, Gibon Y, Nagel A, Meyer S, Krüger P, Selbig J, Müller LA, Rhee SY, Stitt M (2004) mapman: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37:914–939. https://doi.org/10.1111/J.1365-313X.2004.02016.X Wu J, Zhu C, Pang J, Zhang X, Yang C, Xia G, Tian Y, He C (2014) OsLOL1, a C2C2-type zinc finger protein, interacts with OsbZIP58 to promote seed germination through the modulation of gibberellin biosynthesis in Oryza sativa. Plant J 80:1118–1130. https://doi.org/10.1111/TPJ.12714 Xie X, Ma X, Zhu Q, Zeng D, Li G, Liu YG (2017) CRISPR-GE: A Convenient Software Toolkit for CRISPR-Based Genome Editing. Mol Plant 10:1246–1249. https://doi.org/10.1016/J.MOLP.2017.06.004 Yaish MW, El-Kereamy A, Zhu T, Beatty PH, Good AG, Bi YM, Rothstein SJ (2010) The APETALA-2-Like Transcription Factor OsAP2-39 Controls Key Interactions between Abscisic Acid and Gibberellin in Rice. PLoS Genet 6:e1001098. https://doi.org/10.1371/JOURNAL.PGEN.1001098 Yu Y, Zhen S, Wang S, Wang Y, Cao H, Zhang Y, Li J, Yan Y (2016) Comparative transcriptome analysis of wheat embryo and endosperm responses to ABA and H2O2 stresses during seed germination. BMC Genomics 17:1–18. https://doi.org/10.1186/S12864-016-2416-9/FIGURES/5 Zhang C, Zhou L, Lu Y, Yang Y, Feng L, Hao W, Li Q, Fan X, Zhao D, Liu Q (2020) Changes in the physicochemical properties and starch structures of rice grains upon pre-harvest sprouting. Carbohydr Polym 234:115893. https://doi.org/10.1016/J.CARBPOL.2020.115893 Zhang H, Li M, He D, Wang K, Yang P (2020) Mutations on ent-kaurene oxidase 1 encoding gene attenuate its enzyme activity of catalyzing the reaction from ent-kaurene to ent-kaurenoic acid and lead to delayed germination in rice. PLoS Genet 16:e1008562. https://doi.org/10.1371/JOURNAL.PGEN.1008562 Zhang J, Liu F, Kuang Y, Luo M, Chu C, Xu F (2025) The fourth exon confers antagonistic activity of OsMFT1 and OsMFT2 in rice pre-harvest sprouting. Crop J 13:135–144. https://doi.org/10.1016/J.CJ.2024.12.008 Zhang Y, Chen B, Xu Z, Shi Z, Chen S, Huang X, Chen J, Wang X (2014) Involvement of reactive oxygen species in endosperm cap weakening and embryo elongation growth during lettuce seed germination. J Exp Bot 65:3189–3200. https://doi.org/10.1093/JXB/ERU167 Zhu Y, Nomura T, Xu Y, Zhang Y, Peng Y, Mao B, Hanada A, Zhou H, Wang R, Li P, Zhu X, Mander LN, Kamiya Y, Yamaguchi S, He Z (2006) ELONGATED UPPERMOST INTERNODE Encodes a Cytochrome P450 Monooxygenase That Epoxidizes Gibberellins in a Novel Deactivation Reaction in Rice. Plant Cell 18:442–456. https://doi.org/10.1105/TPC.105.038455 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFiguresandTables.zip Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 01 Sep, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviews received at journal 22 Jul, 2025 Reviewers agreed at journal 11 Jul, 2025 Reviewers invited by journal 24 Jun, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 22 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6950427","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476361822,"identity":"5f339434-ac04-49d1-b4a5-46605fb3438e","order_by":0,"name":"Man Bo Lee","email":"","orcid":"","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Man","middleName":"Bo","lastName":"Lee","suffix":""},{"id":476361823,"identity":"c6da4699-cacc-490b-af3a-d04ab5ceec1e","order_by":1,"name":"Ha Neul Lee","email":"","orcid":"","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Ha","middleName":"Neul","lastName":"Lee","suffix":""},{"id":476361824,"identity":"e96a2195-b7af-4cb9-968e-4e3560d15596","order_by":2,"name":"Sang-Ho Chu","email":"","orcid":"","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Sang-Ho","middleName":"","lastName":"Chu","suffix":""},{"id":476361825,"identity":"276f3311-9b2c-4528-9666-63e5be0d5d13","order_by":3,"name":"Yong-Jin Park","email":"","orcid":"","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Yong-Jin","middleName":"","lastName":"Park","suffix":""},{"id":476361826,"identity":"dca7cbb1-1bc1-4ad7-9b6d-d898cb0758cb","order_by":4,"name":"Jae Yoon Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACxgYIbcDGwHwYxGCG8A8QpYUtmTgtMGDAwMBjjMTHo4W5/fAxiQ8Vd4z5xM58Nvi4o5bd4ADzww8MZ+7hdlhPWprkjDPPzNikczcnzjxznNngAJuxBMONYjx+yTGT5m07bAPScpi37RhQC4MZA8OHBNxa+t9/g2rJeQzVwv4Nv5YZOWwgLUCH5TAn87bVALXwAG25gU/LM2PLGWcOG7NJpxkbzmw7wCx5mKdYIuEMbi2G/ckPb3yoOGw4f3byY4mPbXXJfMfbN374cAyPlgYGFgkk/uFkcGTi1sDAIA+Mmg9I/Do7PIpHwSgYBaNghAIA2ehVFz9/WlIAAAAASUVORK5CYII=","orcid":"","institution":"Kongju National University","correspondingAuthor":true,"prefix":"","firstName":"Jae","middleName":"Yoon","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-06-22 15:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6950427/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6950427/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85562417,"identity":"c8273e14-e5b7-4d12-8721-8abc9798bc4e","added_by":"auto","created_at":"2025-06-27 13:31:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10265,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eOsERF94\u003c/em\u003e as a candidate gene involved in pre-harvest sprouting. Boxplots exhibit the effects of different haplotypes of \u003cem\u003eOsERF94\u003c/em\u003e on pre-harvest sprouting. Different lowercase letters indicate significant differences between haplotypes based on Scheffé’s test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/9a137c1a6fee483607cef420.png"},{"id":85563148,"identity":"ce7d32ef-3fdc-473a-9072-fa8a4a8a639d","added_by":"auto","created_at":"2025-06-27 13:39:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19606,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of \u003cem\u003eOsERF94\u003c/em\u003e and the CRISPR/Cas9 vector. (\u003cstrong\u003eA\u003c/strong\u003e) A schematic diagram of \u003cem\u003eOsERF94\u003c/em\u003e and the target sequences of each sgRNA. The blue box indicates the exon, and gray boxes indicate the untranslated regions. The black arrows indicate the locations of the target sequences of the sgRNAs. PAM sequences are shown in red. (\u003cstrong\u003eB\u003c/strong\u003e) A schematic diagram of the T-DNA region of the CRISPR/Cas9 vector. The gray arrows indicate the target sequences of \u003cem\u003eHpt\u003c/em\u003e-specific primers and \u003cem\u003eCas9\u003c/em\u003e-specific primers. LB, left border; Poly(A), poly(A) tails; \u003cem\u003eHpt\u003c/em\u003e, \u003cem\u003ehygromycin phosphotransferase\u003c/em\u003e; 35S-P, cauliflower mosaic virus 35S promoter; \u003cem\u003eOsU3\u003c/em\u003e-P,rice \u003cem\u003eU3\u003c/em\u003e promoter; \u003cem\u003eNos\u003c/em\u003e-T, \u003cem\u003enopaline synthase\u003c/em\u003e terminator; RB, right border\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/7f4dbb8a32ef784e81b39649.png"},{"id":85563459,"identity":"0aa17ab3-dcd0-4b8e-a10c-55b264696f8e","added_by":"auto","created_at":"2025-06-27 13:47:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":359145,"visible":true,"origin":"","legend":"\u003cp\u003eMutations in \u003cem\u003eOsERF94\u003c/em\u003e induced by CRISPR/Cas9. (\u003cstrong\u003eA\u003c/strong\u003e) A 1 bp insertion of thymine, induced by sgRNA2, was identified within \u003cem\u003eOsERF94\u003c/em\u003e in 1-I-ET by Sanger sequencing. PAM sequences are indicated in red. (\u003cstrong\u003eB\u003c/strong\u003e) A 2 bp deletion (TA), induced by sgRNA3, was identified in 2-D-ET. T\u003csub\u003e1\u003c/sub\u003e transgene-free mutants were selected using PCR screening with \u003cem\u003eHpt\u003c/em\u003e-specific and \u003cem\u003eCas9\u003c/em\u003e-specific primers in 1-I-ET (\u003cstrong\u003eC\u003c/strong\u003e) and 2-D-ET (\u003cstrong\u003eD\u003c/strong\u003e), respectively. Amino acid sequences of the WT, 1-I-ET, and 2-D-ET were aligned (\u003cstrong\u003eE\u003c/strong\u003e). The 1 bp insertion in 1-I-ET and the 2 bp deletion in 2-D-ET resulted in early termination, as indicated by the red arrows. An ethylene-responsive transcription factor and an AP2/ERF domain superfamily were predicted by InterProScan in \u003cem\u003eOsERF94\u003c/em\u003e. The ethylene-responsive transcription factor is highlighted in the orange box, and the AP2/ERF domain superfamily is highlighted in the blue box. \u003cem\u003eHpt\u003c/em\u003e, \u003cem\u003ehygromycin phosphotransferase\u003c/em\u003e; PC, positive control\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/16633ad454ef4a3f96dfccd7.png"},{"id":85564088,"identity":"2f55656e-6aae-40fa-89b8-3b0813558f7b","added_by":"auto","created_at":"2025-06-27 13:55:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":328868,"visible":true,"origin":"","legend":"\u003cp\u003eIncreased pre-harvest sprouting in \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines. Ten and nine panicles were collected from ‘Nipponbare’ at five and six weeks after heading, respectively. Seeds of the WT were germinated for seven days, and pictures were taken (\u003cstrong\u003eA\u003c/strong\u003e, \u003cstrong\u003eB\u003c/strong\u003e). The germination rate of the WT was evaluated daily for seven days (\u003cstrong\u003eC\u003c/strong\u003e). Ten and eleven panicles were collected from WT, 1-I-ET, and 2-D-ET at five weeks after heading, respectively. Seeds of the WT and gene-edited lines were germinated for seven days, and pictures were taken (\u003cstrong\u003eD\u003c/strong\u003e). The germination rate of the WT and gene-edited lines was evaluated daily for seven days (\u003cstrong\u003eE\u003c/strong\u003e). Error bars represent the standard error. Asterisks indicate significant differences compared to panicles collected from ‘Nipponbare’ at five weeks, as determined by Student’s \u003cem\u003et\u003c/em\u003e-test (* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001)\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/0ecc3a75a71e9fac8362da86.png"},{"id":85563149,"identity":"6bcc1487-0b6e-479a-a258-737017fefad6","added_by":"auto","created_at":"2025-06-27 13:39:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":102389,"visible":true,"origin":"","legend":"\u003cp\u003eExpression analysis of \u003cem\u003eOsERF94\u003c/em\u003e and transcriptomic profiling of \u003cem\u003eOsERF94\u003c/em\u003e mutants. (\u003cstrong\u003eA\u003c/strong\u003e) Gene expression levels of \u003cem\u003eOsERF94\u003c/em\u003e are presented as log\u003csub\u003e2\u003c/sub\u003e(TPM + 1), from 80 RNA sequencing libraries available at the Rice Genome Annotation Project (https://rice.uga.edu/index.shtml). Bars indicate average values, and error bars represent standard deviations. (\u003cstrong\u003eB\u003c/strong\u003e) The relative expression levels of \u003cem\u003eOsERF94\u003c/em\u003e during grain development were quantified via qRT-PCR. The \u003cem\u003eOsActin\u003c/em\u003e gene served as an internal control. Error bars represent the standard error of the mean of three biological replicates. An asterisk indicates a significant difference compared to samples collected one week after heading, as determined by the Student’s \u003cem\u003et\u003c/em\u003e-test (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05)\u003cem\u003e. \u003c/em\u003e(\u003cstrong\u003eC\u003c/strong\u003e) Venn diagram of DEGs identified from RNA-sequencing of seeds collected three weeks after heading from 1-I-ET, 2-D-ET, and the WT. DEGs were defined by a comparison between each gene-edited line and the WT. (\u003cstrong\u003eD\u003c/strong\u003e) MapMan visualization of DEGs commonly identified in both gene-edited lines, categorized under ‘Regulation overview’. Red boxes indicate up-regulated DEGs, and blue boxes indicate down-regulated DEGs. The scale bar represents fold change values\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/76050db741a0fd8202a94a50.png"},{"id":85562420,"identity":"cf84d049-3924-4548-b559-0cc886fb7997","added_by":"auto","created_at":"2025-06-27 13:31:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":74560,"visible":true,"origin":"","legend":"\u003cp\u003eGibberellin (GA) and ethylene biosynthesis pathway and differential gene expression in \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines. (\u003cstrong\u003eA\u003c/strong\u003e) GA biosynthesis begins with \u003cem\u003etrans\u003c/em\u003e-geranylgeranyl diphosphate (GGPP), which is converted to \u003cem\u003eent\u003c/em\u003e-kaurene and further processed into the active forms GA\u003csub\u003e1\u003c/sub\u003e and GA\u003csub\u003e4\u003c/sub\u003e by GA20ox and GA3ox. (\u003cstrong\u003eB\u003c/strong\u003e) Ethylene biosynthesis is initiated by the conversion of methionine into \u003cem\u003eS\u003c/em\u003e-adenosyl-methionine (SAM) via the enzyme \u003cem\u003eS\u003c/em\u003e-adenosyl-methionine synthetase (SAMS). SAM is then transformed into the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) through the catalytic activity of ACC synthase (ACS). Subsequently, ACC is oxidized to ethylene by the action of ACC oxidase (ACO). DEGs simultaneously identified in the gene-edited plants are shown in italics, and the fold changes of the DEGs were visualized as a heatmap with the following color scale: red for up-regulation and blue for down-regulation. 3 indicates samples collected three weeks after heading, while P0, P1, and P2 indicate samples collected at zero, one, and two days after the PHS treatment using panicles collected five weeks after heading\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/8ecb34782c0abf647553d81c.png"},{"id":85564229,"identity":"4a65221d-9060-4dca-93b4-0786dd083ddf","added_by":"auto","created_at":"2025-06-27 14:03:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1949135,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/9af08841-1f99-481d-ae19-d07382d9399b.pdf"},{"id":85562430,"identity":"dfeb438c-8a47-4d68-bd7a-aa54cc231bcb","added_by":"auto","created_at":"2025-06-27 13:31:32","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3601153,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiguresandTables.zip","url":"https://assets-eu.researchsquare.com/files/rs-6950427/v1/2a1fd0a060948de2de0f6519.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Pre-harvest Sprouting via Regulation of GA Biosynthesis and Deactivation in Rice","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePre-harvest sprouting (PHS) refers to a phenomenon where seeds germinate on the panicles before harvest under continuously rainy and humid weather (Li et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). PHS has become a serious global issue during the agricultural production of cereal crops such as rice, with the average annual financial loss due to PHS has been estimated to be one billion dollars worldwide (Tai et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hull et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). PHS also affects grain quality by enhancing the activity of oxidoreductases and hydrolases in cereal grains, resulting in the loss of nutrients such as starch, protein, and oil (Li et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The eating and cooking quality of rice grains were lower in rice plants affected by PHS, as were the amylose and total starch contents (Zhang C et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, cultivated crops generally exhibit lower dormancy levels compared to their wild ancestors, which makes modern crop varieties more susceptible to PHS (Tai et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Due to global climate change, heavy rainfall in specific regions can lead to more frequent occurrences of PHS (Hu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, developing PHS-resistant varieties has become a key objective in rice-breeding programs, alongside the discovery of PHS-resistant genes (Lee et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePHS occurs primarily due to an imbalanced dormancy/germination ratio (Tai et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Seed dormancy and germination are distinct biochemical and physiological processes regulated by various internal factors, such as plant hormones, carbohydrate metabolites, and reactive oxygen species (Hilhorst and Karssen \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Omoarelojie et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Among plant hormones, abscisic acid (ABA) and gibberellin (GA) play critical roles in antagonistically controlling dormancy and germination (Yaish et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sohn et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). ABA promotes dormancy formation and maintenance, whereas GA induces germination by counteracting ABA effects on dormancy (Finkelstein et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In rice, \u003cem\u003eOsVP1\u003c/em\u003e activates \u003cem\u003eSdr4\u003c/em\u003e, a key regulator of pre-harvest sprouting, by binding to its promoter (Chen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eOsVP1\u003c/em\u003e and \u003cem\u003eSdr4\u003c/em\u003e play roles in the biosynthesis and signaling pathways of ABA and GA, regulating seed dormancy. A rice mutant with delayed germination and semi-dwarfism was identified, caused by mutations in \u003cem\u003eOsKO1\u003c/em\u003e (Zhang H et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The mutation inhibits GA biosynthesis, impairing starch mobilization and reducing ABA signaling, ultimately delaying seed germination.\u003c/p\u003e \u003cp\u003eEthylene also plays important roles in the regulation of dormancy and germination (Corbineau et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The \u003cem\u003eArabidopsis reduced dormancy 3\u003c/em\u003e mutant is caused by a loss-of-function mutant of the ethylene receptor ETHYLENE RESPONSE1 (ETR1) (Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). ETR1 regulates seed dormancy and germination partially through the DELAY OF GERMINATION1 pathway. Ethylene counteracts the inhibitory effects of ABA on germination by modulating ABA metabolism and signaling pathways (Linkies and Leubner-Metzger \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Additionally, ethylene and GA work synergistically to promote seed germination (Corbineau et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Ethylene response factors (ERFs), a family of APETALA2/ETHYLENE RESPONSE FACTORS (AP2/ERFs), regulate genes involved in hormone and stress signaling (M\u0026uuml;ller and Munn\u0026eacute;-Bosch \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Phukan et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Previously, we identified \u003cem\u003eOsERF1\u003c/em\u003e and \u003cem\u003eOsERF94\u003c/em\u003e through a genome-wide association study (GWAS) of PHS and germination from detached grains (Min et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). \u003cem\u003eOsERF1\u003c/em\u003e and \u003cem\u003eOsERF94\u003c/em\u003e were detected within a 100 kb region from the SNP marker Chr4_Pos27378200, which was detected in Manhattan plots for both traits. Furthermore, \u003cem\u003eOsERF1\u003c/em\u003e was functionally validated using the CRISPR-Cas9/HDR and geminiviral replicon system in rice (Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The ERF1-hdr line, which carries a 1 bp SNP and a 6 bp insertion in \u003cem\u003eOsERF1\u003c/em\u003e, exhibited enhanced seed dormancy and PHS resistance. Genes involved in ABA signaling, such as \u003cem\u003ePYL\u003c/em\u003e, \u003cem\u003eSnRK2\u003c/em\u003e, \u003cem\u003eABI3\u003c/em\u003e, \u003cem\u003eABI5\u003c/em\u003e, and \u003cem\u003eSdr4\u003c/em\u003e, were highly expressed in the ERF1-hdr line compared to the WT, whereas genes related to ethylene and GA signaling, such as \u003cem\u003eEIN3\u003c/em\u003e, \u003cem\u003eGID1\u003c/em\u003e, and \u003cem\u003eGYMYB\u003c/em\u003e, showed reduced expression levels.\u003c/p\u003e \u003cp\u003eThe Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system has been extensively utilized for targeted gene editing in plants (Bortesi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In rice, CRISPR/Cas9 gene editing has been applied for gene-function analyses and for the development of stress-resistant varieties, including those resistant to PHS (Romero and Gatica-Arias \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The CRISPR/Cas9 gene editing of \u003cem\u003eOsABA8ox\u003c/em\u003e resulted in frameshift mutations in gene-edited rice lines (Fu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Loss-of-function in \u003cem\u003eOsABA8ox\u003c/em\u003e enhances seed dormancy by elevating endogenous ABA levels and modulating ABA signaling. Overexpression and CRISPR/Cas9 gene editing of \u003cem\u003eOsMFT2\u003c/em\u003e, which encodes a phosphatidylethanolamine-binding protein, resulted in different responses to PHS (Zhang et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Overexpression lines exhibited strong seed dormancy and weak PHS, whereas gene-edited lines showed strong PHS.\u003c/p\u003e \u003cp\u003eIn this study, we applied CRISPR/Cas9 gene editing to \u003cem\u003eOsERF94\u003c/em\u003e, which was identified along with \u003cem\u003eOsERF1\u003c/em\u003e in our previous GWAS of PHS (Min et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), to investigate its function. \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines exhibited increased PHS compared to non-edited \u0026lsquo;Nipponbare\u0026rsquo; plants. We conducted RNA sequencing of \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines and the WT to investigate the molecular mechanisms by which \u003cem\u003eOsERF94\u003c/em\u003e regulates PHS. \u003cem\u003eOsERF94\u003c/em\u003e, a PHS-resistant gene, can be utilized in molecular breeding programs to enhance PHS resistance in rice. Additionally, our transcriptome analysis provides valuable insights into the role of \u003cem\u003eOsERF94\u003c/em\u003e in regulating PHS.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eOsERF94\u003c/b\u003e, \u003cb\u003ea Candidate Gene Associated with Pre-harvest Sprouting in Rice\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA previous GWAS of PHS and detached grain germination was conducted using 127 cultivated rice accessions (Min et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These accessions were subjected to whole-genome sequencing and variant calling to obtain genotype data. GWAS was conducted using a compressed mixed linear model in the GAPIT package. SNPs exceeding a \u0026ndash;log\u003csub\u003e10\u003c/sub\u003e(\u003cem\u003eP\u003c/em\u003e-value) threshold of 5 were considered statistically significant. A total of 15 significant SNPs were associated with PHS, and 76 were linked to detached grain germination. The SNP marker Chr4_Pos27378200, located on chromosome 4 at position 27378200, was significantly associated with both traits. Within a 100 kb region surrounding the significant SNP, 25 genes were identified, including \u003cem\u003eOsERF94\u003c/em\u003e (\u003cem\u003eOs04g0547600\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eSubsequently, we investigated haplotypes of \u003cem\u003eOsERF94\u003c/em\u003e to examine the impact on PHS. Haplotype 1 of \u003cem\u003eOsERF94\u003c/em\u003e exhibits three SNPs, one of which results in a non-synonymous mutation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), whereas haplotype 6 shows the same sequence as the reference. PHS was significantly reduced in haplotype 1 compared to haplotype 6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). GWAS and haplotype analyses suggested that \u003cem\u003eOsERF94\u003c/em\u003e is a candidate gene associated with PHS in rice. To validate this hypothesis, we generated \u003cem\u003eOsERF94\u003c/em\u003e loss-of-function mutants in the \u0026lsquo;Nipponbare\u0026rsquo; background using CRISPR/Cas9 gene editing.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSNPs identified in haplotype 1 of \u003cem\u003eOsERF94\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubstitution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAmino acid change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMutation type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePosition on chromosome 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP to P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSynonymous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27409430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV to V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSynonymous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27409520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eA to T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-synonymous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27409731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDevelopment of\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e \u003cb\u003eMutant Lines via CRISPR/Cas9\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eOsERF94\u003c/em\u003e contains a single exon, and three guide sequences were designed to target the exon for CRISPR/Cas9 gene editing (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The CRISPR-P v2.0 (Liu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the CRISPR RGEN tools (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) were used for guide sequence design. The two guide sequences of sgRNA1 and sgRNA2 target the same position on the target gene, but the first nucleotide (5\u0026prime; end) of the guide sequence of sgRNA2 was changed to adenine instead of cytosine (as in sgRNA1 and the WT). The first nucleotide of the guide sequence of sgRNA3 was also changed to adenine. Each guide sequence was introduced into the pRGEB31 vector (Addgene #51295) and driven by the \u003cem\u003eOsU3\u003c/em\u003e promoter (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The expression levels of \u003cem\u003eCas9\u003c/em\u003e and \u003cem\u003eHpt\u003c/em\u003e were driven by separate 35S promoters.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 81 transgenic plants were obtained through \u003cem\u003eAgrobacterium\u003c/em\u003e-mediated transformation using mature seeds of \u0026lsquo;Nipponbare\u0026rsquo;. To identify mutations in \u003cem\u003eOsERF94\u003c/em\u003e, PCR was performed using \u003cem\u003eOsERF94\u003c/em\u003e-specific primers (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) on T\u003csub\u003e0\u003c/sub\u003e plants, followed by Sanger sequencing of the PCR products. The mutation types of T\u003csub\u003e0\u003c/sub\u003e plants were determined by manually analyzing the Sanger sequencing results, which were then double-checked using the ICE tool (Roginsky \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The mutation efficiency of sgRNA1 was 25.64% (10 out of 39), whereas sgRNA2 exhibited a mutation efficiency rate of 72.73% (16 out of 22) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results suggest that the \u003cem\u003eU3\u003c/em\u003e promoter prefers adenine as the transcription initiation site. The mutation efficiency of sgRNA3 was 35.00% (7 out of 20). Heterozygous mutations (54.55%) were the most frequently found mutation type, with 18 heterozygous mutants identified among the 33 T\u003csub\u003e0\u003c/sub\u003e mutant lines (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Homozygous mutations were identified in five out of the 33 T\u003csub\u003e0\u003c/sub\u003e mutant lines. Among them, four lines harbored homozygous mutations induced by sgRNA2, while one line carried a homozygous mutation induced by sgRNA3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMutation efficiency rates of guide sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMutation efficiency (%)\u003csup\u003ez\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10/39 (25.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16/22 (72.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7/20 (35.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ez\u003c/sup\u003e The mutation efficiency of each guide sequence was calculated by dividing the number of gene-edited plants by the number of transgenic plants\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of Mutation Types in T\u003csub\u003e0\u003c/sub\u003e Mutant Plants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHomozygous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHeterozygous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eBi-allelic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eNon-determined\u003csup\u003ez\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo. of plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo. of plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo. of plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esgRNA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003ez\u003c/sup\u003e Multi-alleic, chimera\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA T\u003csub\u003e0\u003c/sub\u003e heterozygous mutant line (#1-g2-C4) induced by sgRNA2 and a T\u003csub\u003e0\u003c/sub\u003e homozygous mutant line (#1-g3-C13) were advanced to the next generation. \u003cem\u003eCas9\u003c/em\u003e-specific and \u003cem\u003eHpt\u003c/em\u003e-specific primers (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) were used to identify transgene-free lines of T\u003csub\u003e1\u003c/sub\u003e #1-g2-C4 and T\u003csub\u003e1\u003c/sub\u003e #1-g3-C13, as the \u003cem\u003eCas9\u003c/em\u003e gene is located near the right border, while the \u003cem\u003eHpt\u003c/em\u003e gene is located near the left border in the pRGEB31 vector (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). PCR-negative lines were selected as transgene-free lines. To identify homozygous mutant lines among the transgene-free lines, Sanger sequencing was conducted. Transgene-free lines of T\u003csub\u003e1\u003c/sub\u003e #1-g2-C4 with a homozygous 1 bp insertion were designated as 1-I-ET, while transgene-free lines of T\u003csub\u003e1\u003c/sub\u003e #1-g3-C13 with a homozygous 2 bp deletion were designated as 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-D). The 1 bp insertion in 1-I-ET and the 2 bp deletion in 2-D-ET caused frameshift mutations in \u003cem\u003eOsERF94\u003c/em\u003e, leading to early termination (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). The ethylene-responsive transcription factor domain is detected between the 102nd and 255th amino acids, and the AP2/ERF domain superfamily is detected between the 137th and 198th amino acids, as determined by InterProScan (Quevillon et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Both the ethylene-responsive transcription factor and the AP2/ERF domain superfamily were removed from the prematurely terminated proteins of 1-I-ET and 2-D-ET, respectively. These results indicate the loss-of-function mutations of \u003cem\u003eOsERF94\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLoss-of-function of\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e \u003cb\u003eEnhances Pre-harvest Sprouting\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo examine the PHS response based on the sampling timing, panicles were collected from \u0026lsquo;Nipponbare\u0026rsquo; plants at five and six weeks after heading and were then subjected to germination experiments (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). When panicles were collected at six weeks after heading, the germination rate was 89.43% at three days after the PHS treatment and exceeded 95% starting from four days after the PHS treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The germination rates were significantly decreased at all time points except one day after PHS in WT panicles collected at five weeks after heading compared to those collected at six weeks. When panicles were collected at five weeks, the germination rate was 85.96% at seven days after the PHS treatment. Because the PHS experiment conducted at five weeks after heading allowed for a more precise observation of germination rates compared to the six-week experiment, subsequent PHS treatments were performed using panicles collected at five weeks after heading. To ascertain the involvement of \u003cem\u003eOsERF94\u003c/em\u003e in PHS in rice, \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines were used for the PHS treatment. Panicles were collected at five weeks after heading from 1-I-ET (ten panicles) and 2-D-ET (eleven panicles). The germination rates were significantly increased at all time points, except for that at one day after PHS in 1-I-ET and 2-D-ET compared to WT panicles collected at five weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). The germination rates of 1-I-ET and 2-D-ET at three days after the PHS treatment were 88.42% and 85.88%, respectively, similar to that (85.96%) of the WT at seven days. These results indicate that the loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e enhances susceptibility to PHS. On the other hand, no drastic phenotypic changes, such as severe dwarfism, were observed in either gene-edited line compared to the WT (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Plant height was slightly reduced in both gene-edited lines.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTranscriptome Analysis of\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, little is known about the expression of \u003cem\u003eOsERF94\u003c/em\u003e in rice. The expression patterns of \u003cem\u003eOsERF94\u003c/em\u003e across different tissues and developmental stages were examined using 80 rice RNA sequencing libraries available from the Rice Genome Annotation Project (RGAP, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rice.uga.edu/index.shtml\u003c/span\u003e\u003cspan address=\"https://rice.uga.edu/index.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Hamilton et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). According to RGAP DB, \u003cem\u003eOsERF94\u003c/em\u003e is relatively highly expressed during the seed development stage compared to the seedling, vegetative, and reproductive stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). \u003cem\u003eOsERF94\u003c/em\u003e expression is particularly high in the endosperm and embryo and is also elevated in mature seeds under hypoxic conditions. Specifically, the embryo RNA sequencing data (SRR9002107 and SRR9002108) were obtained from \u0026lsquo;Nipponbare\u0026rsquo; embryos collected at 15 days after pollination, consistent with the cultivar used in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate the expression pattern of \u003cem\u003eOsERF94\u003c/em\u003e further during grain development, RNA samples were collected at weekly intervals for four consecutive weeks starting one week after heading. \u003cem\u003eOsERF94\u003c/em\u003e was highly expressed at three weeks after heading, and the expression level was significantly higher than that at one week after heading (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In contrast, \u003cem\u003eOsERF94\u003c/em\u003e was barely expressed at one and two weeks after heading, with CT values of qRT-PCR greater than 35. Therefore, we performed RNA sequencing using samples collected at three weeks after heading, when the expression level of \u003cem\u003eOsERF94\u003c/em\u003e was the highest.\u003c/p\u003e \u003cp\u003eUsing seeds collected three weeks after heading, RNA sequencing was conducted to investigate the role of \u003cem\u003eOsERF94\u003c/em\u003e in PHS. Differentially expressed genes (DEGs) were identified by comparing each gene-edited line with the WT, using a threshold of |fold change| \u0026ge; 2 and false discovery rate (FDR) \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;0.05. A total of 3445 DEGs were identified in 1-I-ET, consisting of 2733 up-regulated and 712 down-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In 2-D-ET, 4863 DEGs were identified, with 3413 up-regulated and 1450 down-regulated genes. The number of DEGs commonly identified in both 1-I-ET and 2-D-ET was 2878. To characterize the biological relevance, a MapMan analysis was conducted using the common DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The average fold change values of the common DEGs between 1-I-ET and 2-D-ET were used for the MapMan analysis (Thimm et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and are presented as red (up-regulated) or blue (down-regulated) in the corresponding MapMan diagram. Within the \u0026lsquo;Regulation overview\u0026rsquo; category, 21 DEGs were identified in the \u0026lsquo;GA\u0026rsquo; subcategory, representing the largest number among the subcategories related to plant hormones. In the \u0026lsquo;ABA\u0026rsquo; subcategory, 13 DEGs were identified, all of which were down-regulated. The majority of these DEGs were related to ribosomal subunits (Table S2). In addition, a number of common DEGs were identified in redox-related subcategories, such as \u0026lsquo;Heme\u0026rsquo;, \u0026lsquo;Glutaredoxin\u0026rsquo;, and \u0026lsquo;Dismutase/Catalase\u0026rsquo;. In the \u0026lsquo;Dismutase/Catalase\u0026rsquo; subcategory, most of the DEGs were associated with the lignin biosynthesis pathway (Table S2).\u003c/p\u003e \u003cp\u003eSeveral genes involved in GA biosynthesis and deactivation were identified among the common DEGs between 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). \u003cem\u003eOsLOL1\u003c/em\u003e (\u003cem\u003eAGIS_Os08g005160\u003c/em\u003e), \u003cem\u003eOsKO3\u003c/em\u003e (\u003cem\u003eAGIS_Os06g033220\u003c/em\u003e), and \u003cem\u003eOsKAO\u003c/em\u003e (\u003cem\u003eAGIS_Os06g000950\u003c/em\u003e) are involved in GA biosynthesis, while \u003cem\u003eOsEUI\u003c/em\u003e (\u003cem\u003eAGIS_Os05g035360\u003c/em\u003e) and \u003cem\u003eOsGA2ox3\u003c/em\u003e (\u003cem\u003eAGIS_Os01g047760\u003c/em\u003e) are involved in GA deactivation. All of the DEGs were up-regulated in both 1-I-ET and 2-D-ET. These results suggest that \u003cem\u003eOsERF94\u003c/em\u003e plays a role in controlling the GA content by regulating both GA biosynthesis and deactivation in developing seeds.\u003c/p\u003e \u003cp\u003eMoreover, additional RNA sequencing was conducted on seeds collected at zero, one, and two days after PHS using panicles harvested five weeks after heading from WT, 1-I-ET, and 2-D-ET. Before PHS, the GA biosynthesis genes \u003cem\u003eOsKO3\u003c/em\u003e and \u003cem\u003eOsKO4\u003c/em\u003e (\u003cem\u003eAGIS_Os06g033150\u003c/em\u003e) were up-regulated in both 1-I-ET and 2-D-ET, while the GA deactivation gene \u003cem\u003eOsGA2ox5\u003c/em\u003e (\u003cem\u003eAGIS_Os07g000350\u003c/em\u003e) was down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). One day after PHS, the GA activation gene \u003cem\u003eOsGA3ox2\u003c/em\u003e (\u003cem\u003eAGIS_Os01g006890\u003c/em\u003e) was up-regulated in both 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Two days after PHS, \u003cem\u003eOsLOL1\u003c/em\u003e, involved in GA biosynthesis, and \u003cem\u003eOsGA2ox1\u003c/em\u003e (\u003cem\u003eAGIS_Os05g005570\u003c/em\u003e), involved in GA deactivation, were both up-regulated in 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). These findings provide further support of the role of \u003cem\u003eOsERF94\u003c/em\u003e in regulating GA during the PHS response.\u003c/p\u003e \u003cp\u003eSeveral genes involved in GA biosynthesis and deactivation were identified among the common DEGs between 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). One day after PHS, the GA activation gene \u003cem\u003eOsGA3ox2\u003c/em\u003e (\u003cem\u003eAGIS_Os01g006890\u003c/em\u003e) was up-regulated in both 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Two days after PHS, \u003cem\u003eOsLOL1\u003c/em\u003e, involved in GA biosynthesis, and \u003cem\u003eOsGA2ox1\u003c/em\u003e (\u003cem\u003eAGIS_Os05g005570\u003c/em\u003e), involved in GA deactivation, were both up-regulated in 1-I-ET and 2-D-ET. These findings provide additional support for the role of \u003cem\u003eOsERF94\u003c/em\u003e in regulating GA during the PHS response. In addition to GA-related genes, several genes involved in ethylene biosynthesis were differentially expressed in both 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). \u003cem\u003eOsACO5\u003c/em\u003e (\u003cem\u003eAGIS_Os05g043260\u003c/em\u003e) and \u003cem\u003eOsACS2\u003c/em\u003e (\u003cem\u003eAGIS_Os04g043000\u003c/em\u003e) were down-regulated at zero and one day after PHS, respectively. In contrast, \u003cem\u003eOsACS1\u003c/em\u003e (\u003cem\u003eAGIS_Os03g044810\u003c/em\u003e) was highly up-regulated in both lines, with fold changes of 144.4 in 1-I-ET and 354.19 in 2-D-ET. These results suggest that \u003cem\u003eOsERF94\u003c/em\u003e also regulates the PHS response by modulating ethylene biosynthesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOff-target Analysis in\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e \u003cb\u003eGene-edited Lines\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe investigated whether the off-target effects of sgRNA2 and sgRNA3 resulted in mutations at off-target candidate sites in T\u003csub\u003e1\u003c/sub\u003e gene-edited lines. Off-target candidate sites of sgRNA2 and sgRNA3 (Table S3) were predicted using CRISPR-GE (Xie et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Whole-genome re-sequencing was conducted on 1-I-ET (#1-g2-C4-31, sgRNA2), 2-D-ET (#1-g3-C13-4, sgRNA3), and the WT, and the reads were mapped to the \u0026lsquo;Nipponbare\u0026rsquo; reference genome. Few or no mutations were identified in any of the off-target candidate sites in both gene-edited lines compared to the WT. In most of the mapped reads, the mapped sequences were identical to those of the reference genome, and only a very small number of reads contained nucleotide substitutions rather than deletions or insertions. These nucleotide substitutions were considered to be sequencing errors. The mapping results of both gene-edited lines for off-target candidates with an off-score greater than 0.1 are presented in Fig. S2. In this study, \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines were generated and validated to lack detectable off-target mutations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eCRISPR/Cas9-mediated Mutagenesis of\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e \u003cb\u003eEnhances Susceptibility to Pre-harvest Sprouting\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCRISPR/Cas9 gene editing has been widely utilized in plant molecular research, as CRISPR/Cas9 enables precise and accurate modifications of target genes (Bortesi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Romero and Gatica-Arias \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We successfully induced mutations in \u003cem\u003eOsERF94\u003c/em\u003e via CRISPR/Cas9-mediated mutagenesis. In T\u003csub\u003e0\u003c/sub\u003e plants, the mutation efficiency rates across all three sgRNAs was 40.74%, with the mutation efficiency rates of sgRNA1 and sgRNA2 being 25.64% and 72.73%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Only one nucleotide differed between the guide sequences of sgRNA1 and sgRNA2. While the guide sequence of sgRNA1 is a perfect match to \u003cem\u003eOsERF94\u003c/em\u003e, that of sgRNA2 has a single mismatch, where the cytosine at the 5\u0026prime; end is substituted with adenine. The mutation efficiency of sgRNA2 was higher than that of sgRNA1 by 47.09%. It is known that the \u003cem\u003eU3\u003c/em\u003e promoter in the CRISPR/Cas9 vector initiates transcription at a defined adenine nucleotide (Belhaj et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The guide sequence of sgRNA2 begins with adenine, which may lead to higher expression of sgRNA2 compared to sgRNA1, thereby resulting in higher mutation efficiency.\u003c/p\u003e \u003cp\u003eAfter advancing a generation, we obtained scientifically reliable transgene-free homozygous gene-edited lines. To confirm transgene-free lines, we performed PCR screening using primers specific to \u003cem\u003eHpt\u003c/em\u003e (near the left border of the CRISPR vector) and \u003cem\u003eCas9\u003c/em\u003e (near the right border). In transgene-free homozygous mutant lines, germination rates were significantly higher than those of the WT (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE), implying that the loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e increases susceptibility to PHS. Our results are consistent with our previous GWAS but appear to be inconsistent with the haplotype analysis of PHS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It seems that the non-synonymous mutation in haplotype 6 enhances PHS resistance in rice, similar to the PHS-resistant allele of \u003cem\u003eOsERF1\u003c/em\u003e, which carries a non-synonymous mutation and a 6 bp insertion (Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The CRISPR-Cas9/HDR and geminiviral replicon system was applied to \u0026lsquo;Dongjin\u0026rsquo;, which does not contain either the non-synonymous mutation or the 6 bp insertion, resulting in the ERF1-hdr line carrying both mutations. PHS resistance was enhanced in the ERF1-hdr line compared to \u0026lsquo;Dongjin\u0026rsquo;. Prime editing or CRISPR-Cas9/HDR gene editing could also be employed in \u0026lsquo;Nipponbare\u0026rsquo; to determine whether \u003cem\u003eOsERF94\u003c/em\u003e haplotype 6 confers PHS resistance. In the present study, CRISPR/Cas9 gene editing of \u003cem\u003eOsERF94\u003c/em\u003e induced early termination, which is expected to abolish the \u003cem\u003eOsERF94\u003c/em\u003e function entirely through complete gene knockout. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, if the gene-edited lines had the haplotype 1 variant, they may exhibit enhanced resistance to PHS. However, because our lines represent a complete knockout, it is possible that they are even more susceptible to PHS than the haplotype 6 lines, which are already known to be PHS-susceptible.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLoss-of-Function of\u003c/b\u003e \u003cb\u003eOsERF94\u003c/b\u003e \u003cb\u003ePromotes PHS by Modulating GA Biosynthetic and Catabolic Genes\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eOsERF94\u003c/em\u003e was involved in regulating both the biosynthesis and deactivation of GAs during seed development. At three weeks after heading, the GA biosynthesis-related genes \u003cem\u003eOsLOL1\u003c/em\u003e, \u003cem\u003eOsKO3\u003c/em\u003e, and \u003cem\u003eOsKAO\u003c/em\u003e, as well as the GA deactivation-related gene \u003cem\u003eOsEUI\u003c/em\u003e, were all up-regulated in both 1-I-ET and 2-D-ET (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). OsLOL1, a C2C2-type finger protein, participates in GA biosynthesis, influencing seed germination in rice (Wu et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). OsLOL1 interacts with OsbZIP58, leading to the activation of the \u003cem\u003eOsKO2\u003c/em\u003e gene, a key gene in GA biosynthesis (Wu et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). A homolog of \u003cem\u003eOsKO2\u003c/em\u003e, \u003cem\u003eOsKO3\u003c/em\u003e, also participates in the GA biosynthesis pathway (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The CRISPR/Cas9-mediated \u003cem\u003eOsKO3\u003c/em\u003e knockout line exhibited delays in both germination and seminal root growth (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). An exogenous GA treatment partially rescued the root growth defect, indicating that the defect is associated with the GA pathway. \u003cem\u003eOsKAO\u003c/em\u003e plays a critical role in GA biosynthesis by catalyzing the formation of GA\u003csub\u003e12\u003c/sub\u003e (Sakamoto et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Unlike other GA-metabolic enzymes encoded by multigene families, \u003cem\u003eOsKAO\u003c/em\u003e is represented by a single gene in rice. Mutation of \u003cem\u003eOsKAO\u003c/em\u003e resulted in a severely dwarfed phenotype and led to a substantial reduction in downstream GAs, including the complete absence of GA\u003csub\u003e1\u003c/sub\u003e in the \u003cem\u003eoskao-1\u003c/em\u003e mutant (Sakamoto et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). \u003cem\u003eOsLOL1\u003c/em\u003e, \u003cem\u003eOsKO3\u003c/em\u003e, and \u003cem\u003eOsKAO\u003c/em\u003e play important roles in GA biosynthesis in rice, and the up-regulation of these genes in both gene-edited lines can contribute to a reduced dormancy level by promoting GA accumulation. However, \u003cem\u003eOsEUI\u003c/em\u003e, a GA catabolic gene, catalyzes the 16\u003cem\u003eα\u003c/em\u003e,17-epoxidation of non-13-hydroxylated GAs (Zhu et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). OsEUI reduces the activity of bioactive GA\u003csub\u003e4\u003c/sub\u003e in rice, demonstrating its role as a GA deactivating enzyme. Given that OsEUI has been reported to suppress GA accumulation and promote seed dormancy, its up-regulation in both gene-edited lines in our study likely contributes to an enhanced level of dormancy by reducing GA accumulation. These findings suggest that \u003cem\u003eOsERF94\u003c/em\u003e regulates GA levels in developing seeds by modulating both GA biosynthesis and catabolism, thereby contributing to the balance between seed dormancy and the germination potential.\u003c/p\u003e \u003cp\u003e \u003cem\u003eOsERF94\u003c/em\u003e regulated seed germination by modulating both GA biosynthesis and deactivation at zero, one, and two days after PHS using panicles harvested five weeks after heading. At five weeks after heading (before PHS), \u003cem\u003eOsKO3\u003c/em\u003e and its homolog \u003cem\u003eOsKO4\u003c/em\u003e were up-regulated in both gene-edited lines, while the GA deactivation gene \u003cem\u003eOsGA2ox5\u003c/em\u003e was down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). GA 2-oxidases play a key role in the GA catabolic pathway, and \u003cem\u003eOsGA2ox5\u003c/em\u003e, a member of the C\u003csub\u003e20\u003c/sub\u003e-GA2ox subfamily, acts on GA\u003csub\u003e12\u003c/sub\u003e and GA\u003csub\u003e53\u003c/sub\u003e to produce GA\u003csub\u003e110\u003c/sub\u003e and GA\u003csub\u003e97\u003c/sub\u003e, respectively (Dong and Zeevaart \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Shan et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). \u003cem\u003eOsGA2ox5\u003c/em\u003e overexpression was shown to result in dwarfism and GA-deficient phenotypes in rice (Shan et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, \u003cem\u003eOsGA3ox2\u003c/em\u003e, which is involved in the production of bioactive GAs, was up-regulated in both gene-edited lines one day after PHS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). \u003cem\u003eOsGA3ox2\u003c/em\u003e encodes an active GA 3β-hydroxylase that catalyzes the conversion of GA\u003csub\u003e20\u003c/sub\u003e and GA\u003csub\u003e9\u003c/sub\u003e into GA\u003csub\u003e1\u003c/sub\u003e and GA\u003csub\u003e4\u003c/sub\u003e, respectively, and is expressed in germinating rice seeds (Itoh et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The up-regulation of GA biosynthesis genes \u003cem\u003eOsKO3\u003c/em\u003e, \u003cem\u003eOsKO4\u003c/em\u003e, and \u003cem\u003eOsGA3ox2\u003c/em\u003e, along with the down-regulation of the GA catabolic gene \u003cem\u003eOsGA2ox5\u003c/em\u003e, likely contributed to increased endogenous GA in seeds, thereby breaking dormancy and promoting germination. The differential expression levels of GA biosynthetic and catabolic genes in the gene-edited lines accelerated germination under PHS conditions. Germination rates were sharply and significantly increased from two days after PHS in both gene-edited lines compared to those of the WT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Taken together, the loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e promotes PHS by modulating GA biosynthesis and catabolism during the early stages of germination.\u003c/p\u003e \u003cp\u003eAt two days after PHS, the GA biosynthesis gene \u003cem\u003eOsLOL1\u003c/em\u003e was up-regulated in both gene-edited lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The up-regulation of \u003cem\u003eOsLOL1\u003c/em\u003e can positively affect PHS. \u003cem\u003eOsLOL1\u003c/em\u003e exhibited high expression in seeds at one day after imbibition (Wu et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In \u003cem\u003eOsLOL1\u003c/em\u003e antisense lines, germination was delayed by three to four days compared to the WT, and the endogenous GA content in imbibed seeds was significantly lower than in the WT. In contrast, the GA deactivation gene \u003cem\u003eOsGA2ox1\u003c/em\u003e was also up-regulated at two days after PHS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). At zero and one days after PHS, the up-regulation of GA biosynthesis genes and the down-regulation of the GA catabolic gene likely led to an increase in endogenous GA levels in the seeds of gene-edited lines. Subsequently, the expression of the GA deactivation gene \u003cem\u003eOsGA2ox1\u003c/em\u003e was up-regulated at two days after PHS, possibly as a feedback response to elevated GA levels, acting to fine-tune GA homeostasis.\u003c/p\u003e \u003cp\u003eThe differential expression levels of ethylene biosynthesis genes in both \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines under PHS conditions appear to contribute to seed germination. Endosperm rupture during seed germination stems from embryo growth and the weakening of the endosperm cap (Zhang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In \u003cem\u003eSisymbrium officinale\u003c/em\u003e, \u003cem\u003eSoACS7\u003c/em\u003e was not expressed before endosperm rupture but was strongly expressed when rupture reached 50\u0026ndash;100% (Iglesias-Fern\u0026aacute;ndez and Matilla \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In our study, seed germination was defined as the point at which the coleoptile length exceeded 2 mm. One day after PHS, the germination rates of 1-I-ET, 2-D-ET, and the WT were 0.32%, 0%, and 0%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). Two days after PHS, the germination rates increased to 58.44% in 1-I-ET, 42.79% in 2-D-ET, and 12.46% in the WT. These results suggest that endosperm rupture occurred more frequently in the gene-edited lines than in the WT on the second day after PHS. Moreover, \u003cem\u003eOsACS1\u003c/em\u003e was strongly up-regulated in both gene-edited lines at two days after PHS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eThe gene expression patterns of GA biosynthesis genes (\u003cem\u003eSoGA3ox2\u003c/em\u003e, \u003cem\u003eSoGA20ox2\u003c/em\u003e, and \u003cem\u003eSoGA2ox6\u003c/em\u003e) and ethylene biosynthesis genes (\u003cem\u003eSoACO2\u003c/em\u003e and \u003cem\u003eSoACS7\u003c/em\u003e) were analyzed during seed germination in \u003cem\u003eSisymbrium officinale\u003c/em\u003e (Iglesias-Fern\u0026aacute;ndez and Matilla \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Seed samples were collected at 0, 6, 12, 18, 20, 22, and 26 hours of germination. Endosperm rupture was observed at 20 hours, reached approximately 50% at 22 hours, and was nearly complete by 26 hours. \u003cem\u003eSoGA3ox2\u003c/em\u003e was strongly expressed at six hours of imbibition, but its expression declined afterward, maintaining about half the level from 12 to 26 hours. In contrast, \u003cem\u003eSoGA2ox6\u003c/em\u003e transcripts were barely detectable at six hours but peaked at 20 and 26 hours. \u003cem\u003eSoACS7\u003c/em\u003e was not expressed before endosperm rupture but showed strong expression at 22 and 26 hours. In our study, \u003cem\u003eOsGA3ox2\u003c/em\u003e was up-regulated one day after PHS in both \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines, while \u003cem\u003eOsGA2ox1\u003c/em\u003e and \u003cem\u003eOsACS1\u003c/em\u003e were strongly up-regulated two days after PHS. This sequential up-regulation pattern of \u003cem\u003eOsGA3ox2\u003c/em\u003e, \u003cem\u003eOsGA2ox1\u003c/em\u003e, and \u003cem\u003eOsACS1\u003c/em\u003e in \u003cem\u003eOsERF94\u003c/em\u003e gene-edited lines, together with the observed germination rates under PHS conditions, closely resembles the sequential expression pattern of \u003cem\u003eSoGA3ox2\u003c/em\u003e, \u003cem\u003eSoGA2ox6\u003c/em\u003e, and \u003cem\u003eSoACS7\u003c/em\u003e during seed germination in \u003cem\u003eSisymbrium officinale\u003c/em\u003e. These findings imply that GA functions earlier than ethylene in the regulation of seed germination. The loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e influences seed germination by modulating the expression of genes involved in GA and ethylene biosynthesis.\u003c/p\u003e \u003cp\u003eIn conclusion, our study demonstrates that the loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e significantly promotes PHS in rice by modulating the expression of GA biosynthetic and catabolic genes. \u003cem\u003eOsERF94\u003c/em\u003e appears to regulate GA accumulation during both seed development and the early stages of germination. The altered expression levels of key GA-related genes, specifically \u003cem\u003eOsLOL1\u003c/em\u003e, \u003cem\u003eOsKO3\u003c/em\u003e, \u003cem\u003eOsGA3ox2\u003c/em\u003e, and \u003cem\u003eOsGA2ox5\u003c/em\u003e, suggest a coordinated mechanism by which \u003cem\u003eOsERF94\u003c/em\u003e balances dormancy and the germination potential. To the best of our knowledge, little is known about the expression patterns and functional roles of \u003cem\u003eERF94\u003c/em\u003e in rice or other plant species. Our findings contribute to a better understanding of the role of \u003cem\u003eERF94\u003c/em\u003e in the hormonal regulation of seed germination. In addition, two PHS-associated genes (\u003cem\u003eOsERF1\u003c/em\u003e and \u003cem\u003eOsERF94\u003c/em\u003e) were identified near the SNP marker Chr4_Pos27378200, providing valuable insights for rice-breeding programs aiming to improve PHS resistance.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePlant Materials and Pre-harvest Sprouting Screening\u003c/h2\u003e \u003cp\u003eRice cultivar \u0026lsquo;Nipponbare\u0026rsquo; (\u003cem\u003eOryza sativa\u003c/em\u003e L., spp. \u003cem\u003ejaponica\u003c/em\u003e) plants were grown in a growth chamber maintained under 12 hours of light (29\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C) and 12 hours of darkness (23\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C). Panicles were collected at 35 and 42 days after heading (DAH) from WT and at 35 DAH from mutant lines induced by CRISPR/Cas9 for PHS screening. The primary branch of the panicle was cut and placed on autoclaved Whatman filter paper No. 1 (Whatman, Little Chalfont, UK) in a petri dish (150 \u0026times; 20 mm), after which an amount of 30 ml of tap water was added to the petri dish. The lid was covered to maintain humidity. The petri dishes, covered with the lids, were placed in a growth chamber maintained at 12 hours of light (29\u0026deg;C, \u0026plusmn; 1) and 12 hours of darkness (23\u0026deg;C, \u0026plusmn; 1). Germination was evaluated every day for seven days using plump seeds, excluding sterile seeds. Seeds were evaluated as germinated when the length of the coleoptile exceeded 2 mm.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCRISPR/Cas9 Vector Construction and Rice Transformation\u003c/h3\u003e\n\u003cp\u003eGuide sequence candidates targeting \u003cem\u003eOsERF94\u003c/em\u003e (\u003cem\u003eOs04g0547600\u003c/em\u003e) were designed using the CRISPR-P v2.0 (Liu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the CRISPR RGEN tools (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Two exon regions of \u003cem\u003eOsERF94\u003c/em\u003e (5\u0026prime;\u0026ndash; CTATGTCGTGGCAAGAGCAG\u003cb\u003eCGG\u003c/b\u003e \u0026minus;\u0026thinsp;3\u0026prime; and 5\u0026prime;\u0026ndash; \u003cb\u003eCCC\u003c/b\u003eGCCTATGTCGTGGCAAGAGC \u0026minus;\u0026thinsp;3\u0026prime;, PAM regions are indicated in bold) were used to design the guide sequences. A total of three guide sequences (sgRNA1 : 5\u0026prime;\u0026ndash; CTATGTCGTGGCAAGAGCAG \u0026minus;\u0026thinsp;3\u0026prime;; sgRNA2 : 5\u0026prime;\u0026ndash; aTATGTCGTGGCAAGAGCAG \u0026minus;\u0026thinsp;3\u0026prime;; 5\u0026prime;\u0026ndash; aCTCTTGCCACGACATAGGC \u0026minus;\u0026thinsp;3\u0026prime;) were designed for CRISPR/Cas9 vector construction using the pRGEB31 plasmid (addgene, #51295). The \u003cem\u003eOsU3\u003c/em\u003e promoter drives the single guide RNA in the pRGEB31 vector. The first nucleotide of sgRNA2 and sgRNA3 was changed to A. sgRNA1 and sgRNA2 target the same position in the \u003cem\u003eOsERF94\u003c/em\u003e exon. Each guide sequence was introduced into the pRGEB31 vector. The CRISPR/Cas9 vectors for \u003cem\u003eOsERF94\u003c/em\u003e gene editing were transformed into the \u003cem\u003eAgrobacterium\u003c/em\u003e strain EHA105 by a freeze\u0026ndash;thaw method (Chen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). \u003cem\u003eAgrobacterium\u003c/em\u003e-mediated transformation using mature seeds of \u0026lsquo;Nipponbare\u0026rsquo; was conducted, as described in earlier work (Lee et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Transformed calli were selected on callus induction media containing 30 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of hygromycin during the first round of selection, and on media containing 50 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of hygromycin during the second round. Shoots were regenerated on shoot induction media containing 50 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of hygromycin at 28℃ under a light/dark cycle (12 hours of day/12 hours of night).\u003c/p\u003e\n\u003ch3\u003eIdentification of Gene-Edited Mutants\u003c/h3\u003e\n\u003cp\u003e Genomic DNA was extracted from young leaves of putative transgenic plants using the HiGene\u0026trade; Genomic DNA Prep kit (BIOFACT, Seoul, Republic of Korea) according to the manufacturer's instructions. PCR was conducted to detect transgenic plants with \u003cem\u003eCas9\u003c/em\u003e-specific primers. To identify mutations in \u003cem\u003eOsERF94\u003c/em\u003e, PCR was conducted with \u003cem\u003eOsERF94\u003c/em\u003e-specific primers using T\u003csub\u003e0\u003c/sub\u003e plants, followed by Sanger sequencing of the PCR products. Mutation types of T\u003csub\u003e0\u003c/sub\u003e plants, such as heterozygous mutation and homozygous mutation, were distinguished by manually analyzing the Sanger sequencing results and were double-checked using the ICE (Inference of CRISPR Edits) tool (Roginsky \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The list of primers for PCR is available in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. PCR was carried out with TaKaRa \u003cem\u003eEx\u003c/em\u003e Taq (Takara Bio, Otsu, Japan) under the following conditions: 95\u0026deg;C for 5 min, followed by 30 cycles of 95\u0026deg;C for 30 sec, 56\u0026ndash;62\u0026deg;C for 30 sec, and 72\u0026deg;C for 1 min, with a final extension at 72\u0026deg;C for 5 min.\u003c/p\u003e \u003cp\u003eTo obtain transgene-free homozygous mutants, genomic DNA was extracted from young leaves of T\u003csub\u003e1\u003c/sub\u003e plants, and PCR was performed with the \u003cem\u003eCas9\u003c/em\u003e-specific primers and \u003cem\u003eHpt\u003c/em\u003e-specific primers. The list of primers for PCR is available in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. PCR-negative plants were selected and used for further PCR with the \u003cem\u003eOsERF94\u003c/em\u003e-specific primers. Sanger sequencing results of the PCR products were analyzed manually and double-checked using the ICE tool.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA Extraction and Quantitative Real‑time PCR\u003c/h2\u003e \u003cp\u003eHulled seeds were collected at 7, 14, 21, 28 DAH from \u0026lsquo;Nipponbare\u0026rsquo; and were frozen in liquid nitrogen. The seeds were ground into a fine powder using a mortar and pestle. Total RNA was extracted using the Ribospin\u0026trade; Seed/Fruit kit (Geneall, Seoul, Republic of Korea) following the manufacturer\u0026rsquo;s instructions. RNA was converted to cDNA by reverse transcription using oligo (dT) primers with the Power cDNA Synthesis Kit (iNtRON Biotechnology, Seoul, Republic of Korea). To evaluate the expression of the \u003cem\u003eOsERF94\u003c/em\u003e gene during seed development, qRT-PCR was performed with the RealMOD\u0026trade; Green W\u003csup\u003e2\u003c/sup\u003e 2x qPCR mix (iNtRON Biotechnology, Seoul, Republic of Korea) on a Rotor-Gene Q machine (QIAGEN, Hilden, Germany). The qRT-PCR conditions were 95℃ for 10 min followed by 40 cycles of 95℃ for 20 sec, 60℃ for 40 sec, and 72\u0026deg;C for 20 sec, with a final extension at 72\u0026deg;C for 5 min. Gene expression levels were normalized to \u003cem\u003eOsACT1\u003c/em\u003e (\u003cem\u003eOs03g0718100\u003c/em\u003e). The primer information is presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Total RNA was extracted from three panicles as biological replicates, and qRT-PCR was conducted with three technical replicates for each sample. Gene expression levels were quantified using the 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method (Livak and Schmittgen \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRNA sequencing\u003c/h3\u003e\n\u003cp\u003eSeeds were collected at 21 DAH from 1-I-ET, 2-D-ET, and the WT, with three biological replicates for each line. Total RNA was isolated using the Ribospin\u0026trade; Seed/Fruit kit (Geneall, Seoul, Republic of Korea) according to the manufacturer\u0026rsquo;s instructions. The total RNA concentration was measured using the Quant-iT RiboGreen RNA Assay kit (Invitrogen, MA, USA). RNA integrity was examined using the TapeStation RNA ScreenTape system (Agilent, CA, USA). High-quality RNA samples with an RIN greater than 7.0 were used to prepare libraries, with 0.5 \u0026micro;g of total RNA per sample, using the TruSeq Stranded Total RNA Library Prep Plant kit (Illumina, CA, USA). Libraries were quantified using the KAPA Library Quantification kit (Kapa Biosystems, MA, USA), and the quality of libraries was evaluated using the D1000 ScreenTape system (Agilent, CA, USA). Indexed libraries were then sequenced in paired-end mode (2\u0026times;150 bp) on an Illumina HiSeq X Ten (Illumina, CA, USA). Adapter sequences and low-quality bases were removed using Trimmomatic v0.38 (Bolger et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Cleaned reads were aligned to the \u003cem\u003eOryza sativa\u003c/em\u003e T2T-NIP reference genome using HISAT2 v2.1.0 (Shang et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). SAM files were sorted and indexed using SAMtools v1.9 (Li et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and transcript assembly and quantification were performed using StringTie v2.1.3b (Pertea et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The gene expression analysis was conducted using DESeq2 (Love et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). DEGs were identified based on the criteria of |fold change| \u0026ge; 2 and FDR \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. For the MapMan analysis (Thimm et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), bincode mapping was conducted using the Mercator webtool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.plabipd.de/portal/mercator-sequence-annotation\u003c/span\u003e\u003cspan address=\"https://www.plabipd.de/portal/mercator-sequence-annotation\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Lohse et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Common DEGs between 1-I-ET and 2-D-ET were selected, and common DEGs with an average fold change greater than 2 were subjected to a MapMan analysis to identify affected metabolic pathways.\u003c/p\u003e \u003cp\u003eAdditionally, seeds were collected at zero, one, and two days after the PHS treatment using panicles harvested at five weeks after heading from 1-I-ET, 2-D-ET, and the WT, with two biological replicates for each line. Total RNA was extracted from each line and was used for RNA sequencing on the same platform described above. DEGs were identified using the criteria of |fold change| \u0026ge; 2 and \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003ch3\u003ePotential Off-targets and Whole-genome Re-sequencing\u003c/h3\u003e\n\u003cp\u003ePotential off-targets of sgRNA2 and sgRNA3 were predicted using CRISPR-GE (Xie et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Two transgene-free homozygous mutant lines, 1-I-ET-31 (#1-g2-C4-31) and 2-D-ET-4 (#1-g3-C13-4), and the WT were used for whole-genome re-sequencing to search for off-targets. Genomic DNA (100 ng) was fragmented and subsequently used for library preparation with the TruSeq Nano DNA Library Prep kit (Illumina, CA, USA) following the manufacturer\u0026rsquo;s protocol. The quality of libraries was examined via electrophoresis using the Agilent High Sensitivity DNA kit (Agilent, CA, USA). Library quantification was performed using the KAPA Library Quantification kit (Kapa Biosystems, MA, USA) according to the manufacturer\u0026rsquo;s protocol. Sequencing was conducted in paired-end mode (2\u0026times;150 bp) on the Illumina NovaSeq X Plus platform (Illumina, CA, USA). The quality of the raw data was evaluated using FastQC. Low-quality reads were trimmed with Cutadapt using a Q20 cutoff and a minimum remaining length of 15 bp. The resulting clean reads were then aligned to the \u0026lsquo;Nipponbare\u0026rsquo; reference genome (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ricesuperpir.com/web/nip\u003c/span\u003e\u003cspan address=\"http://www.ricesuperpir.com/web/nip\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Shang et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) using BWA and were visualized with Geneious Prime v2023.0.4.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAbscisic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAP2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAPETALA2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDAH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDays after heading\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDifferentially expressed gene\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eERF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEthylene response factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFalse discovery rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGibberellin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGWAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGenome-wide association study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePre-harvest sprouting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRGAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRice Genome Annotation Project\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe online version contains supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely appreciate Dr. Laehyeon Cho and his lab members (Pusan National University, Republic of Korea) for their technical support with rice tissue culturing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSHC, YJP, and JYK developed the original concept of the project, and MBL and JYK designed the experiments. MBL generated the CRISPR/Cas9 gene-edited lines and conducted the majority of the experiments. HNL participated in the identification of gene-edited lines and in the qRT-PCR analysis. MBL drafted the manuscript, and all the authors contributed to manuscript revision and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the R\u0026amp;D program for Rural Development Administration (RDA), Republic of Korea (Project No. RS-2024-00322431), the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (Project No. 2022R1A4A1030348).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBelhaj K, Chaparro-Garcia A, Kamoun S, Nekrasov V (2013) Plant genome editing made easy: Targeted mutagenesis in model and crop plants using the CRISPR/Cas system. Plant Methods 9:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1746-4811-9-39/TABLES/2\u003c/span\u003e\u003cspan address=\"10.1186/1746-4811-9-39/TABLES/2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114\u0026ndash;2120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/BIOINFORMATICS/BTU170\u003c/span\u003e\u003cspan address=\"10.1093/BIOINFORMATICS/BTU170\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBortesi L, Zhu C, Zischewski J, Perez L, Bassi\u0026eacute; L, Nadi R, Forni G, Lade SB, Soto E, Jin X, Medina V, Villorbina G, Mu\u0026ntilde;oz P, Farr\u0026eacute; G, Fischer R, Twyman RM, Capell T, Christou P, Schillberg S (2016) Patterns of CRISPR/Cas9 activity in plants, animals and microbes. Plant Biotechnol J 14:2203\u0026ndash;2216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/PBI.12634\u003c/span\u003e\u003cspan address=\"10.1111/PBI.12634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen H, Nelson RS, Sherwood JL (1994) Enhanced recovery of transformants of Agrobacterium tumefaciens after freeze-thaw transformation and drug selection. Biotechniques 16:664\u0026ndash;668\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen W, Wang W, Lyu Y, Wu Y, Huang P, Hu S, Wei X, Jiao G, Sheng Z, Tang S, Shao G, Luo J (2021) OsVP1 activates Sdr4 expression to control rice seed dormancy via the ABA signaling pathway. Crop J 9:68\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.CJ.2020.06.005\u003c/span\u003e\u003cspan address=\"10.1016/J.CJ.2020.06.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Tian X, Xue L, Zhang X, Yang S, Brian Traw M, Huang J (2019) CRISPR-Based Assessment of Gene Specialization in the Gibberellin Metabolic Pathway in Rice. Plant Physiol 180:2091\u0026ndash;2105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1104/PP.19.00328\u003c/span\u003e\u003cspan address=\"10.1104/PP.19.00328\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorbineau F, Xia Q, Bailly C, El-Maarouf-Bouteau H (2014) Ethylene, a key factor in the regulation of seed dormancy. Front Plant Sci 5:113486. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/FPLS.2014.00539/PDF\u003c/span\u003e\u003cspan address=\"10.3389/FPLS.2014.00539/PDF\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong JL, Zeevaart JAD (2005) Molecular Cloning of GA 2-Oxidase3 from Spinach and Its Ectopic Expression in Nicotiana sylvestris. Plant Physiol 138:243\u0026ndash;254. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1104/PP.104.056499\u003c/span\u003e\u003cspan address=\"10.1104/PP.104.056499\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinkelstein R, Reeves W, Ariizumi T, Steber C (2008) Molecular aspects of seed dormancy. Annu Rev Plant Biol 59:387\u0026ndash;415. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/ANNUREV.ARPLANT.59.032607.092740/CITE/REFWORKS\u003c/span\u003e\u003cspan address=\"10.1146/ANNUREV.ARPLANT.59.032607.092740/CITE/REFWORKS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu K, Song W, Chen C, Mou C, Huang Y, Zhang F, Hao Q, Wang P, Ma T, Chen Y, Zhu Z, Zhang M, Tong Q, Liu X, Jiang L, Wan J (2022) Improving pre-harvest sprouting resistance in rice by editing OsABA8ox using CRISPR/Cas9. Plant Cell Rep 41:2107\u0026ndash;2110. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S00299-022-02917-3/METRICS\u003c/span\u003e\u003cspan address=\"10.1007/S00299-022-02917-3/METRICS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamilton JP, Li C, Buell CR (2025) The rice genome annotation project: an updated database for mining the rice genome. Nucleic Acids Res 53:D1614\u0026ndash;D1622. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/NAR/GKAE1061\u003c/span\u003e\u003cspan address=\"10.1093/NAR/GKAE1061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHilhorst HWM, Karssen CM (1992) Seed dormancy and germination: the role of abscisic acid and gibberellins and the importance of hormone mutants. Plant Growth Regul 11:225\u0026ndash;238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00024561/METRICS\u003c/span\u003e\u003cspan address=\"10.1007/BF00024561/METRICS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHull SI, Swanepoel PA, Botes WC (2024) A critical review of the factors influencing pre-harvest sprouting of wheat. Agron J 116:3354\u0026ndash;3367. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/AGJ2.21701\u003c/span\u003e\u003cspan address=\"10.1002/AGJ2.21701\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Y, Sang Y, Li M, Hu W, Liu B, Huang P, Kang D, Liu Y, Min D, Song Y (2025) J Agron Crop Sci 211:e70041. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/JAC.70041\u003c/span\u003e\u003cspan address=\"10.1111/JAC.70041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Evaluating Wheat Pre-Harvest Sprouting Risk Using Indicator Based on Meteorological Data From 1981 to 2020 in China\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIglesias-Fern\u0026aacute;ndez R, Matilla AJ (2010) Genes involved in ethylene and gibberellins metabolism are required for endosperm-limited germination of Sisymbrium officinale L. seeds. Planta 231:653\u0026ndash;664. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S00425-009-1073-5/FIGURES/5\u003c/span\u003e\u003cspan address=\"10.1007/S00425-009-1073-5/FIGURES/5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eItoh H, Ueguchi-Tanaka M, Sentoku N, Kitano H, Matsuoka M, Kobayashi M (2001) Cloning and functional analysis of two gibberellin 3β-hydroxylase genes that are differently expressed during the growth of rice. Proc Natl Acad Sci U S A 98:8909\u0026ndash;8914. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/PNAS.141239398/ASSET/D7E87D9D-B4FD-4755-89A9-A776421F9723/ASSETS/GRAPHIC/PQ1412393004.JPEG\u003c/span\u003e\u003cspan address=\"10.1073/PNAS.141239398/ASSET/D7E87D9D-B4FD-4755-89A9-A776421F9723/ASSETS/GRAPHIC/PQ1412393004.JPEG\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim JH, Yu J, Kim JY, Park YJ, Bae S, Kang KK, Jung YJ (2024) Phenotypic characterization of pre-harvest sprouting resistance mutants generated by the CRISPR/Cas9-geminiviral replicon system in rice. BMB Rep 57:79. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5483/BMBREP.2023-0210\u003c/span\u003e\u003cspan address=\"10.5483/BMBREP.2023-0210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JS, Chebotarov D, McNally KL, Pede V, Setiyono TD, Raquid R, Hyun WJ, Jeung JU, Kohli A, Mo Y (2021) Novel sources of pre-harvest sprouting resistance for japonica rice improvement. Plants 10:1709. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/PLANTS10081709/S1\u003c/span\u003e\u003cspan address=\"10.3390/PLANTS10081709/S1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee S, Jeon J-S, Jung K-H, An G (1999) Binary vectors for efficient transformation of rice. J Plant Biology 42:310\u0026ndash;316. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF03030346\u003c/span\u003e\u003cspan address=\"10.1007/BF03030346\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi C, Ni P, Francki M, Hunter A, Zhang Y, Schibeci D, Li H, Tarr A, Wang J, Cakir M, Yu J, Bellgard M, Lance R, Appels R (2004) Genes controlling seed dormancy and pre-harvest sprouting in a rice-wheat-barley comparison. Funct Integr Genomics 4:84\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10142-004-0104-3/FIGURES/7\u003c/span\u003e\u003cspan address=\"10.1007/S10142-004-0104-3/FIGURES/7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078\u0026ndash;2079. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/BIOINFORMATICS/BTP352\u003c/span\u003e\u003cspan address=\"10.1093/BIOINFORMATICS/BTP352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLinkies A, Leubner-Metzger G (2011) Beyond gibberellins and abscisic acid: how ethylene and jasmonates control seed germination. Plant Cell Rep 31:253\u0026ndash;270. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S00299-011-1180-1\u003c/span\u003e\u003cspan address=\"10.1007/S00299-011-1180-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, Ding Y, Zhou Y, Jin W, Xie K, Chen LL (2017) CRISPR-P 2.0: An Improved CRISPR-Cas9 Tool for Genome Editing in Plants. Mol Plant 10:530\u0026ndash;532. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.molp.2017.01.003\u003c/span\u003e\u003cspan address=\"10.1016/j.molp.2017.01.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLivak KJ, Schmittgen TD (2001) Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2\u0026thinsp;\u0026ndash; ∆∆CT Method. Methods 25:402\u0026ndash;408. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/METH.2001.1262\u003c/span\u003e\u003cspan address=\"10.1006/METH.2001.1262\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Chen T, Li Y, Wang Z, Cao H, Chen F, Li Y, Soppe WJ, Li W, Liu Y (2019) ETR1/RDO3 Regulates Seed Dormancy by Relieving the Inhibitory Effect of the ERF12-TPL Complex on DELAY OF GERMINATION1 Expression. Plant Cell 31:832\u0026ndash;847. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1105/TPC.18.00449\u003c/span\u003e\u003cspan address=\"10.1105/TPC.18.00449\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLohse M, Nagel A, Herter T, May P, Schroda M, Zrenner R, Tohge T, Fernie AR, Stitt M, Usadel B (2014) Mercator: A fast and simple web server for genome scale functional annotation of plant sequence data. Plant Cell Environ 37:1250\u0026ndash;1258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/PCE.12231/SUPPINFO\u003c/span\u003e\u003cspan address=\"10.1111/PCE.12231/SUPPINFO\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLove MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:1\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/S13059-014-0550-8/FIGURES/9\u003c/span\u003e\u003cspan address=\"10.1186/S13059-014-0550-8/FIGURES/9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMin MH, Khaing AA, Chu SH, Nawade B, Park YJ (2024) Exploring the genetic basis of pre-harvest sprouting in rice through a genome-wide association study-based haplotype analysis. J Integr Agric 23:2525\u0026ndash;2540. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.JIA.2023.12.004\u003c/span\u003e\u003cspan address=\"10.1016/J.JIA.2023.12.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller M, Munn\u0026eacute;-Bosch S (2015) Ethylene Response Factors: A Key Regulatory Hub in Hormone and Stress Signaling. Plant Physiol 169:32\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1104/PP.15.00677\u003c/span\u003e\u003cspan address=\"10.1104/PP.15.00677\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmoarelojie LO, Kulkarni MG, Finnie JF, van Staden J (2022) Smoke-derived cues in the regulation of seed germination: are Ca2+-dependent signals involved? Plant Growth Regul 97:343\u0026ndash;355. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10725-021-00745-1/METRICS\u003c/span\u003e\u003cspan address=\"10.1007/S10725-021-00745-1/METRICS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark J, Bae S, Kim JS (2015) Cas-Designer: a web-based tool for choice of CRISPR-Cas9 target sites. Bioinformatics 31:4014\u0026ndash;4016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/BIOINFORMATICS/BTV537\u003c/span\u003e\u003cspan address=\"10.1093/BIOINFORMATICS/BTV537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL (2015) StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33:290\u0026ndash;295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nbt.3122\u003c/span\u003e\u003cspan address=\"10.1038/nbt.3122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhukan UJ, Jeena GS, Tripathi V, Shukla RK (2017) Regulation of Apetala2/Ethylene response factors in plants. Front Plant Sci 8:238455. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/FPLS.2017.00150/PDF\u003c/span\u003e\u003cspan address=\"10.3389/FPLS.2017.00150/PDF\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R, Mulder J, Attwood TK, Bairoch A, Bateman A, Binns D, Bradley P, Bork P, Bucher P (2005) InterProScan: protein domains identifier. Nucleic Acids Res 33:W116\u0026ndash;W120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/NAR/GKI442\u003c/span\u003e\u003cspan address=\"10.1093/NAR/GKI442\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoginsky J (2018) Analyzing CRISPR editing results. Genetic Eng Biotechnol News 38:S24\u0026ndash;S26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1089/GEN.38.11.13/ASSET/GEN.38.11.13.FP.PNG_V03\u003c/span\u003e\u003cspan address=\"10.1089/GEN.38.11.13/ASSET/GEN.38.11.13.FP.PNG_V03\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomero FM, Gatica-Arias A (2019) CRISPR/Cas9: Development and Application in Rice Breeding. Rice Sci 26:265\u0026ndash;281. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.RSCI.2019.08.001\u003c/span\u003e\u003cspan address=\"10.1016/J.RSCI.2019.08.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakamoto T, Miura K, Itoh H, Tatsumi T, Ueguchi-Tanaka M, Ishiyama K, Kobayashi M, Agrawal GK, Takeda S, Abe K, Miyao A, Hirochika H, Kitano H, Ashikari M, Matsuoka M (2004) An Overview of Gibberellin Metabolism Enzyme Genes and Their Related Mutants in Rice. Plant Physiol 134:1642\u0026ndash;1653. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1104/PP.103.033696\u003c/span\u003e\u003cspan address=\"10.1104/PP.103.033696\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShan C, Mei Z, Duan J, Chen H, Feng H, Cai W (2014) OsGA2ox5, a Gibberellin Metabolism Enzyme, Is Involved in Plant Growth, the Root Gravity Response and Salt Stress. PLoS ONE 9:e87110. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/JOURNAL.PONE.0087110\u003c/span\u003e\u003cspan address=\"10.1371/JOURNAL.PONE.0087110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShang L, He W, Wang T, Yang Y, Xu Q, Zhao X, Yang L, Zhang H, Li X, Lv Y, Chen W, Cao S, Wang X, Zhang B, Liu X, Yu X, He H, Wei H, Leng Y, Shi C, Guo M, Zhang Z, Zhang B, Yuan Q, Qian H, Cao X, Cui Y, Zhang Q, Dai X, Liu C, Guo L, Zhou Y, Zheng X, Ruan J, Cheng Z, Pan W, Qian Q (2023) A complete assembly of the rice Nipponbare reference genome. Mol Plant 16:1232\u0026ndash;1236. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.molp.2023.08.003\u003c/span\u003e\u003cspan address=\"10.1016/j.molp.2023.08.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSohn SI, Pandian S, Kumar TS, Zoclanclounon YAB, Muthuramalingam P, Shilpha J, Satish L, Ramesh M (2021) Seed Dormancy and Pre-Harvest Sprouting in Rice\u0026mdash;An Updated Overview. Int J Mol Sci 22:11804. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/IJMS222111804\u003c/span\u003e\u003cspan address=\"10.3390/IJMS222111804\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTai L, Wang HJ, Xu XJ, Sun WH, Ju L, Liu WT, Li WQ, Sun J, Chen KM (2021) Pre-harvest sprouting in cereals: genetic and biochemical mechanisms. J Exp Bot 72:2857\u0026ndash;2876. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/JXB/ERAB024\u003c/span\u003e\u003cspan address=\"10.1093/JXB/ERAB024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThimm O, Bl\u0026auml;sing O, Gibon Y, Nagel A, Meyer S, Kr\u0026uuml;ger P, Selbig J, M\u0026uuml;ller LA, Rhee SY, Stitt M (2004) mapman: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37:914\u0026ndash;939. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/J.1365-313X.2004.02016.X\u003c/span\u003e\u003cspan address=\"10.1111/J.1365-313X.2004.02016.X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Zhu C, Pang J, Zhang X, Yang C, Xia G, Tian Y, He C (2014) OsLOL1, a C2C2-type zinc finger protein, interacts with OsbZIP58 to promote seed germination through the modulation of gibberellin biosynthesis in Oryza sativa. Plant J 80:1118\u0026ndash;1130. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/TPJ.12714\u003c/span\u003e\u003cspan address=\"10.1111/TPJ.12714\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie X, Ma X, Zhu Q, Zeng D, Li G, Liu YG (2017) CRISPR-GE: A Convenient Software Toolkit for CRISPR-Based Genome Editing. Mol Plant 10:1246\u0026ndash;1249. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.MOLP.2017.06.004\u003c/span\u003e\u003cspan address=\"10.1016/J.MOLP.2017.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYaish MW, El-Kereamy A, Zhu T, Beatty PH, Good AG, Bi YM, Rothstein SJ (2010) The APETALA-2-Like Transcription Factor OsAP2-39 Controls Key Interactions between Abscisic Acid and Gibberellin in Rice. PLoS Genet 6:e1001098. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/JOURNAL.PGEN.1001098\u003c/span\u003e\u003cspan address=\"10.1371/JOURNAL.PGEN.1001098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu Y, Zhen S, Wang S, Wang Y, Cao H, Zhang Y, Li J, Yan Y (2016) Comparative transcriptome analysis of wheat embryo and endosperm responses to ABA and H2O2 stresses during seed germination. BMC Genomics 17:1\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/S12864-016-2416-9/FIGURES/5\u003c/span\u003e\u003cspan address=\"10.1186/S12864-016-2416-9/FIGURES/5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C, Zhou L, Lu Y, Yang Y, Feng L, Hao W, Li Q, Fan X, Zhao D, Liu Q (2020) Changes in the physicochemical properties and starch structures of rice grains upon pre-harvest sprouting. Carbohydr Polym 234:115893. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.CARBPOL.2020.115893\u003c/span\u003e\u003cspan address=\"10.1016/J.CARBPOL.2020.115893\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Li M, He D, Wang K, Yang P (2020) Mutations on ent-kaurene oxidase 1 encoding gene attenuate its enzyme activity of catalyzing the reaction from ent-kaurene to ent-kaurenoic acid and lead to delayed germination in rice. PLoS Genet 16:e1008562. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/JOURNAL.PGEN.1008562\u003c/span\u003e\u003cspan address=\"10.1371/JOURNAL.PGEN.1008562\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Liu F, Kuang Y, Luo M, Chu C, Xu F (2025) The fourth exon confers antagonistic activity of OsMFT1 and OsMFT2 in rice pre-harvest sprouting. Crop J 13:135\u0026ndash;144. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.CJ.2024.12.008\u003c/span\u003e\u003cspan address=\"10.1016/J.CJ.2024.12.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Chen B, Xu Z, Shi Z, Chen S, Huang X, Chen J, Wang X (2014) Involvement of reactive oxygen species in endosperm cap weakening and embryo elongation growth during lettuce seed germination. J Exp Bot 65:3189\u0026ndash;3200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/JXB/ERU167\u003c/span\u003e\u003cspan address=\"10.1093/JXB/ERU167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Y, Nomura T, Xu Y, Zhang Y, Peng Y, Mao B, Hanada A, Zhou H, Wang R, Li P, Zhu X, Mander LN, Kamiya Y, Yamaguchi S, He Z (2006) ELONGATED UPPERMOST INTERNODE Encodes a Cytochrome P450 Monooxygenase That Epoxidizes Gibberellins in a Novel Deactivation Reaction in Rice. Plant Cell 18:442\u0026ndash;456. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1105/TPC.105.038455\u003c/span\u003e\u003cspan address=\"10.1105/TPC.105.038455\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"rice","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rice","sideBox":"Learn more about [Rice](http://thericejournal.springeropen.com)","snPcode":"12284","submissionUrl":"https://submission.nature.com/new-submission/12284/3","title":"Rice","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"OsERF94, CRISPR/Cas9, Pre-harvest sprouting, Germination, GA biosynthesis, GA deactivation","lastPublishedDoi":"10.21203/rs.3.rs-6950427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6950427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePre-harvest sprouting (PHS), where seeds germinate on panicles before harvest under humid conditions, is a serious global issue in cereal crop production, including rice. \u003cem\u003eOsERF94\u003c/em\u003e was previously identified as a candidate gene associated with PHS through a genome-wide association study. In this study, we investigated the role of \u003cem\u003eOsERF94\u003c/em\u003e in PHS using CRISPR/Cas9 gene editing. The CRISPR/Cas9-mediated mutagenesis of \u003cem\u003eOsERF94\u003c/em\u003e induced frameshift mutations, resulting in a loss-of-function of \u003cem\u003eOsERF94\u003c/em\u003e in the 1-I-ET and 2-D-ET lines. The 1-I-ET and 2-D-ET lines exhibited significantly higher germination rates under PHS conditions compared to the wild type, indicating increased susceptibility to PHS. Whole-genome re-sequencing confirmed that few or no mutations could be detected at off-target candidate sites in both edited lines, ensuring the precision of the CRISPR/Cas9 gene editing. A transcriptome analysis revealed that \u003cem\u003eOsERF94\u003c/em\u003e modulates the expression of key GA biosynthetic and catabolic genes, including \u003cem\u003eOsLOL1\u003c/em\u003e, \u003cem\u003eOsKO3\u003c/em\u003e, \u003cem\u003eOsGA3ox2\u003c/em\u003e, and \u003cem\u003eOsGA2ox5\u003c/em\u003e, during both seed development and the early germination stages of PHS. The up-regulation of GA biosynthetic genes and the down-regulation of GA deactivation genes in both gene-edited lines likely led to elevated endogenous GA levels at 0 and 1 days after PHS, promoting germination under PHS conditions. These findings suggest that \u003cem\u003eOsERF94\u003c/em\u003e acts as a negative regulator of germination by modulating both GA biosynthesis and deactivation. Our findings contribute to expanding our knowledge of the molecular mechanisms of \u003cem\u003eOsERF94\u003c/em\u003e in PHS and highlight \u003cem\u003eOsERF94\u003c/em\u003e as a promising target for the genetic improvement of PHS resistance in rice-breeding programs.\u003c/p\u003e","manuscriptTitle":"CRISPR/Cas9-mediated Mutagenesis of OsERF94 Enhances Pre-harvest Sprouting via Regulation of GA Biosynthesis and Deactivation in Rice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-27 13:31:28","doi":"10.21203/rs.3.rs-6950427/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-01T07:37:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T10:20:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302670388645690656339223738835516209244","date":"2025-08-15T02:20:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-22T14:21:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107618521501443374365528319517761991094","date":"2025-07-11T07:18:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-25T02:08:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T13:04:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T13:02:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Rice","date":"2025-06-22T15:32:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"rice","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rice","sideBox":"Learn more about [Rice](http://thericejournal.springeropen.com)","snPcode":"12284","submissionUrl":"https://submission.nature.com/new-submission/12284/3","title":"Rice","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b2f0d099-8e1c-47c3-99d1-129a077b60de","owner":[],"postedDate":"June 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T10:25:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-27 13:31:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6950427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6950427","identity":"rs-6950427","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}